10.7923/6Z9M-WZ55
Olsoy, Peter
Peter
Olsoy
https://orcid.org/0000-0002-8785-0459
Boise State University
Sorensen Forbey, Jennifer
Jennifer
Sorensen Forbey
https://orcid.org/0000-0001-6069-4049
Boise State University
Shipley, Lisa
Lisa
Shipley
Washington State University
Rachlow, Janet
Janet
Rachlow
https://orcid.org/0000-0001-8810-9614
University of Idaho
Robb, Brecken
Brecken
Robb
https://orcid.org/0000-0001-9016-249X
Boise State University
Nobler, Jordan
Jordan
Nobler
Boise State University
Thornton, Daniel
Daniel
Thornton
Washington State University
Data from: Mapping foodscapes and sagebrush morphotypes with unmanned aerial systems for multiple herbivores
University of Idaho
2022
Dataset
FOS: Earth and related environmental sciences
FOS: Biological sciences
FOS: Environmental engineering
en
https://doi.org/10.1007/s10980-020-00990-1
Mapping foodscapes and sagebrush morphotypes with unmanned aerial systems for multiple herbivores
632MB
txt
csv
r
tif
Creative Commons Attribution 4.0 International
Context
The amount and composition of phytochemicals in forage plants influences habitat quality for wild herbivores. However, evaluating forage quality at fine resolutions across broad spatial extents (i.e., foodscapes) is challenging. Unmanned aerial systems (UAS) provide an avenue for bridging this gap in spatial scale.
Objectives
We evaluated the potential for UAS technology to accurately predict nutritional quality of sagebrush (Artemisia spp.) across landscapes. We mapped seasonal forage quality across two sites in Idaho, USA, with different mixtures of species but similar structural morphotypes of sagebrush.
Methods
We classified the sagebrush at both study sites using structural features of shrubs with object-based image analysis and machine learning and linked this classification to field measurements of phytochemicals to interpolate a foodscape for each phytochemical with regression kriging. We compared fine-scale landscape patterns of phytochemicals between sites and seasons.
Results
Classification accuracy for morphotypes was high at both study sites (81–87%). Forage quality was highly variable both within and among sagebrush morphotypes. Coumarins were the most accurately mapped (r2 = 0.57–0.81), whereas monoterpenes were the most variable and least explained. Patches with higher crude protein were larger and more connected in summer than in winter.
Conclusions
UAS allowed for a rapid collection of imagery for mapping foodscapes based on the phytochemical composition of sagebrush at fine scales but relatively broad extents. However, results suggest that a more advanced sensor (e.g., hyperspectral camera) is needed to map mixed species of sagebrush or to directly measure forage quality.
Data Usage Notes
Spatial Reference
NAD83 UTM Zone 11N [Camas]/12N [Cedar Gulch]
Patch Type Classifications
25-cm resolution, classes are 3=on mound, 4=off mound, 5=dwarf. On-mound refers to mima mounds with deeper soils that pygmy rabbits use to dig their burrows and are dominated by big sagebrush (Artemisia tridentata), while off-mound refers to patches dominated by big sagebrush but not on mima mounds, while dwarf patches are dominated by short-statured sagebrush species (e.g., black sagebrush [A. nova], low sagebrush [A. arbuscula]).
Maps of Phytochemistry
25-cm resolution and were generated with regression kriging using the patch type layer and point values from leaf chemistry. Phytochemicals: Crude Protein, Coumarins, Total Monoterpenes, Chemical Diversity of Monoterpenes and two individual monoterpenes (1,8-cineole and camphor). If there was no spatial autocorrelation present in the semivariogram, then maps were not generated for that phytochemical.
Idaho (USA)
-114.35388
-113.18686
43.180083
44.796898
National Science Foundation
https://doi.org/10.13039/100000001
OIA‐1757324
RII Track-1: Linking Genome to Phenome to Predict Adaptive Responses of Organisms to Changing Landscapes
National Science Foundation
https://doi.org/10.13039/100000001
DEB-1146368
Collaborative Research: Modeling the Tradeoffs within Food-, Fear-, and Thermal-Scapes to Explain Habitat Use by Mammalian Herbivores
National Science Foundation
https://doi.org/10.13039/100000001
DEB-1146194
Collaborative Research: Modeling the Tradeoffs within Food-, Fear-, and Thermal-Scapes to Explain Habitat Use by Mammalian Herbivores
National Science Foundation
https://doi.org/10.13039/100000001
IOS-1258217
Courtship Negotiation in a Life-history Context: Interaction between on- and off-lek Tactics in Sage-grouse
National Science Foundation
https://doi.org/10.13039/100000001
OIA-1826801
RII Track-2 FEC: Genomics Underlying Toxin Tolerance (GUTT): Identifying Molecular Innovations that Predict Phenotypes of Toxin Tolerance in Wild Vertebrate Herbivores