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Abstract Structural diversity—the volume and physical arrangement of vegetation within the three‐dimensional (3D) space of ecosystems—is a predictor of ecosystem function that can be measured at large scales with remote sensing. However, the landscape composition and configuration of structural diversity across macrosystems have not been well described. Using a relatively recently developed method to quantify landscape composition and configuration of continuous habitat or terrain, we propose the application of gradient surface metrics (GSMs) to quantify landscape patterns of structural diversity and provide insights into how its spatial pattern relates to ecosystem function. We first applied an example set of GSMs that represent landscape heterogeneity, dominance, and edge density to Lidar‐derived structural diversity within 28 forested landscapes at National Ecological Observatory Network (NEON) sites. Second, we tested for forest type, geographic location, and climate drivers of macroscale variation in GSMs of structural diversity (GSM‐SD). Third, we demonstrated the utility of these metrics for understanding spatial patterns of ecosystem function in a case study with NDVI, a proxy of productivity. We found that GSM‐SD varied in landscapes within macrosystems, with forest type, geographic location, and climate being significantly related to some but not all metrics. We also found that dominance of high peaks of height and vertical complexity of canopy vegetation and the heterogeneity of the vertical complexity and coefficient of variation of canopy vegetation height within 120‐m patches were negatively correlated with NDVI across the 28 NEON sites. However, forest type always had a significant interaction term between these GSM‐SD and NDVI relationships. Our study demonstrates that GSMs are useful to describe the landscape composition and configuration of structural diversity and its relationship with productivity that warrants further consideration for spatially motivated management decisions.
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The geodiv r package: Tools for calculating gradient surface metrics
1. The geodiv r package calculates gradient surface metrics from imagery and other gridded datasets to provide continuous measures of landscape heterogeneity for landscape pattern analysis. 2. geodiv is the first open-source, command line toolbox for calculating many gradient surface metrics and easily integrates parallel computing for applications with large images or rasters (e.g. remotely sensed data). All functions may be applied either globally to derive a single metric for an entire image or locally to create a texture image over moving windows of a user-defined extent. 3. We present a comprehensive description of the functions available through geodiv. A supplemental vignette provides an example application of geodiv to the fields of landscape ecology and biogeography. 4. geodiv allows users to easily retrieve estimates of spatial heterogeneity for a variety of purposes, enhancing our understanding of how environmental structure influences ecosystem processes. The package works with any continuous imagery and may be widely applied in many fields where estimates of surface complexity are useful.
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- PAR ID:
- 10297530
- Editor(s):
- Goslee, Sarah
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 0
- Issue:
- 0
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 1-7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/2041-210X.13677
