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 <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10980_2025_2081_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$\times$</EquationSource> <EquationSource Format="MATHML"><math> <mo>×</mo> </math></EquationSource> </InlineEquation> 3 to 101 <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10980_2025_2081_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$\times$</EquationSource> <EquationSource Format="MATHML"><math> <mo>×</mo> </math></EquationSource> </InlineEquation> 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 <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10980_2025_2081_Article_IEq3.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$\times$</EquationSource> <EquationSource Format="MATHML"><math> <mo>×</mo> </math></EquationSource> </InlineEquation> 81 to 101 <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10980_2025_2081_Article_IEq4.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$\times$</EquationSource> <EquationSource Format="MATHML"><math> <mo>×</mo> </math></EquationSource> </InlineEquation> 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.

Landscape scale effects of primary productivity on forest bird species occurrence and abundance in Argentina

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2025年3月19日

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Ashley M. Olah,
Volker C. Radeloff,
Akash Anand,
Eduarda M. O. Silveira,
Natalia Politi,
Luis Rivera,
Sebastián Martinuzzi,
Guillermo Martínez Pastur,
Anna M. Pidgeon

摘要

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 $\times$ $\times$ 3 to 101 $\times$ $\times$ 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 $\times$ $\times$ 81 to 101 $\times$ $\times$ 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.