Ochotona macrotis
Univariate models - Comparison of univariate models at
different scales prior to model building revealed that the variables low
percentage cover of vegetation, greater percentage of rocks, greater
percentage of large sized rocks, and more number of large-sized rocks
were important for predicting the presence of OM across all scales
(Table C1). It also indicated unique variables that were important at
each spatial scale (Table C1):
- At the Ladakh scale, presence was associated with a greater slope.
- At the South-East Ladakh scale, presence was associated with more
extensive coverage of class 2 rocks (+).
- At the North-West Ladakh scale, presence was associated with
consistently lower NDVI.
All the univariate models run are presented here (Table S3, Table S4,
Table S5).
Multivariate models - At each spatial scale, models
constructed were subjected to a stepwise regression analysis to pick the
best additive models using different methods. The purposeful modeling
approach (Model 2) consistently produced the best models across spatial
scales. It included variables significantly associated with presence in
univariate regressions at regional scales, such as the percentage cover
of large-sized rocks and the number of large-sized rocks (Table 1). At
the Ladakh spatial scale, the presence of OM was driven by a higher
cover of large rocks, a greater number of large-sized rocks, and lower
NDVI in summer (Table 1). At the South-East Ladakh spatial scale, the
occurrence was primarily driven by a higher cover of large rocks, a
greater number of large-sized rocks, higher elevation, lower cover of
shrubs, and consistently low NDVI in winter (Table 1). At the North-West
Ladakh scale, the occurrence was driven by many variables, with no
variables related to rocks, vegetation, or geographic features strongly
influencing the presence of the species (Table 1).