Context: Approaches estimating landscape effects on biodiversity frequently focus on a single extent, finding one 'optimal' extent, or use narrow extents. However, species perceive the environment in different ways, select habitat hierarchically, and respond to multiple selection pressures at extents that best predict each pressure.
Objective: We aimed to assess multi-scale relationships between primary productivity and species occurrences and abundances.
Methods: We used a multi-scale approach, called 'scalograms', to assess landscape level effects of primary productivity, in the form of Dynamic Habitat Indices (DHIs) on the occurrences and abundances of 100 Argentinian forest bird species. We used average DHI values within multiple extents (3 3 to 101 101 pixels; 30 m resolution), and 11 'scalogram' metrics as environmental inputs in occurrence and abundance models.
Results: Average cumulative DHI values in extents 81 81 to 101 101 pixels (5.9 - 9.2 km2) and maximum cumulative DHI across extents were in the top three predictors of species occurrences (included in models for 41% and 18% of species, respectively). Average cumulative DHI values in various extents contributed ~ 1.6 times more predictive power to occurrence models than expected. For species abundances, average DHI values and scalogram measures were in the top three predictors for < 2% of species and contributed less model predictive power than expected, regardless of DHI type (cumulative, minimum, variation).
Conclusions: Argentinian forest bird occurrences, but not abundances, respond to high levels of primary productivity at multiple, broad extents rather than a single 'optimal' extent. Factors other than primary productivity appear to be more important for predicting abundance.
Supplementary information: The online version contains supplementary material available at 10.1007/s10980-025-02081-5.
Keywords: Avian abundance; Avian occurrence; Dynamic Habitat Indices; Landsat; Landscape effect; Scalograms; Spatial scale.
© The Author(s) 2025.