Fine spatial scale assessment of structure and configuration of vegetation cover for northern bobwhites in grazed pastures

• Published in: Ecological processes Vol. 13; no. 1; p. 64
• Main Authors: Avila-Sanchez, J. Silverio, Perotto-Baldivieso, Humberto L., Massey, Lori D., Ortega-S, J. Alfonso, Brennan, Leonard A., Hernández, Fidel
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024; Springer Nature B.V; SpringerOpen
• Subjects: Arid zones; Canopy height model; class; Colinus virginianus; Configuration management; Data collection; Dormancy; Earth and Environmental Science; Environment; forage; Grazing; Ground cover; Growing season; Habitats; Height; Heterogeneity; Image height classification; Image resolution; Imagery; Information management; Information processing; Landscape; Landscape metrics; landscapes; Livestock; Livestock grazing; Nature conservation; Normalized digital surface model; Pasture; pastures; Plant cover; Range management; Rangelands; Remote sensing; Sampling methods; Seasons; soil; Soil management; Spatial distribution; Spatial heterogeneity; Spatiotemporal data; Sustainability management; temporal variation; Temporal variations; Texas; Unmanned aerial vehicles; Vegetation; Vegetation cover; vegetation structure; Wildlife conservation; Wildlife habitats; Wildlife management; Winter; Texas; Canopy height model; Spatial heterogeneity; Normalized digital surface model; Image height classification; Landscape metrics
• ISSN: 2192-1709; 2192-1709
• DOI: 10.1186/s13717-024-00546-0

Background Monitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat. Traditional ground-based sampling methods have been widely used and provide valuable information; however, they are time-consuming, labor-intensive, and limited in their ability to capture larger extents of the spatial and temporal dynamics of rangeland ecosystems. Drones provide a solution to collect data to larger extents than field-based methods and with higher-resolution than traditional remote sensing platforms. Our objectives were to (1) assess the accuracy of vegetation cover height in grasses using drones, (2) quantify the spatial distribution of vegetation cover height in grazed and non-grazed pastures during the dormant (fall–winter) and growing seasons (spring–summer), and (3) evaluate the spatial distribution of vegetation cover height as a proxy for northern bobwhite ( Colinus virginianus ) habitat in South Texas. We achieved this by very fine scale drone-derived imagery and using class level landscape metrics to assess vegetation cover height configuration. Results Estimated heights from drone imagery had a significant relationship with the field height measurements in September ( r 2  = 0.83; growing season) and February ( r 2  = 0.77; dormant season). Growing season pasture maintained residual landscape habitat configuration adequate for bobwhites throughout the fall and winter of 2022–2023 following grazing. Dormant season pasture had an increase in bare ground cover, and a shift from many large patches of tall herbaceous cover (40–120 cm) to few large patches of low herbaceous cover (5–30 cm) ( p  < 0.05). Conclusions Drones provided high-resolution imagery that allowed us to assess the spatial and temporal changes of vertical herbaceous vegetation structure in a semi-arid rangeland subject to grazing. This study shows how drone imagery can be beneficial for wildlife conservation and management by providing insights into changes in fine-scale vegetation spatial and temporal heterogeneity from livestock grazing.