4.7 Article

Lidar provides novel insights into the effect of pixel size and grazing intensity on measures of spatial heterogeneity in a native bunchgrass ecosystem

期刊

REMOTE SENSING OF ENVIRONMENT
卷 235, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2019.111432

关键词

Lidar; Spatial heterogeneity; Semivariograms; Grasslands; Grazing; Aboveground biomass

资金

  1. The Nature Conservacy's Oren Pollak Student Research Grant
  2. Priscilla Bullitt Collins Trust Northwest Conservation Fund
  3. The Nature Conservancy
  4. Oregon Chapter of TNC

向作者/读者索取更多资源

There is a strong link between vegetation heterogeneity and biodiversity in grassland ecosystems. However, quantifying spatial patterns of key metrics, such as aboveground biomass, at landscape scales remains a challenge. This stems from difficulties in accurately estimating grassland biomass at fine scales over large areas and determining what spatial scale is most appropriate to monitor how grassland impacts (e.g., livestock grazing) affect spatial patterns of biomass (i.e., spatial heterogeneity). Here, we use lidar metrics (volume, max height, and intensity) in Random Forest models to quantify fine-resolution (pixel size 1.0668 m (3.5 ft)) aboveground biomass estimates (pseudo R-2 = 0.59; RMSD = 139.4 g m(-2)) across a bunchgrass prairie grassland system. To determine both the effects of grazing on the spatial heterogeneity of aboveground biomass and which pixel size is most sensitive to the effects of livestock grazing on grassland heterogeneity, we aggregated fine-resolution biomass maps to coarser pixel resolutions (3 m, 5 m, 8 m, 20 m, 30 m) across 23 pastures with varying levels of grazing intensity. Following aggregation to coarser pixel resolutions, we observed that semivariogram models produced statistically different (alpha = 0.05) measures of biomass heterogeneity. The range statistic was the only pasture-level semivariogram metric sensitive to grazing, and this relationship was only significant when using the finer-resolution datasets (similar to 1 m to 8 m pixels). Our results demonstrate 1) the applicability of lidar data for quantifying biomass in short-statured grasslands, 2) that grazing in pacific northwest bunchgrass prairie can decrease spatial heterogeneity of aboveground biomass and 3) that fine-resolution satellite data ( < 10 m pixel sizes) are necessary to effectively monitor the effects of grazing on the spatial heterogeneity of vegetation biomass, an indirect metric of biodiversity at management scales (pasture sizes ranged from 40 to 745 ha) in this grassland ecosystem.

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