Journal
ECOLOGY AND EVOLUTION
Volume 8, Issue 4, Pages 1974-1983Publisher
WILEY
DOI: 10.1002/ece3.3417
Keywords
boosted regression tree models; clay; field estimation; Gamma radiometric data; particle size analysis; potassium; remote sensing; sand; soil texture; thorium
Categories
Funding
- Centre of Excellence for Environmental Decisions
- Australian Research Council
Ask authors/readers for more resources
Plant ecologists require spatial information on functional soil properties but are often faced with soil classifications that are not directly interpretable or useful for statistical models. Sand and clay content are important soil properties because they indicate soil water-holding capacity and nutrient content, yet these data are not available for much of the landscape. Remotely sensed soil radiometric data offer promise for developing statistical models of functional soil properties applicable over large areas. Here, we build models linking radiometric data for an area of 40,000km(2) with soil physicochemical data collected over a period of 30years and demonstrate a strong relationship between gamma radiometric potassium (K-40), thorium (Th-232), and soil sand and clay content. Our models showed predictive performance of 43% with internal cross-validation (to held-out data) and similar to 30% for external validation to an independent test dataset. This work contributes to broader availability and uptake of remote sensing products for explaining patterns in plant distribution and performance across landscapes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available