4.7 Article

Integrated Analysis of Productivity and Biodiversity in a Southern Alberta Prairie

Journal

REMOTE SENSING
Volume 8, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/rs8030214

Keywords

biomass; eddy covariance; remote sensing; grassland; biodiversity

Funding

  1. iCORE
  2. AITF
  3. Rangeland Research Institute
  4. CFI
  5. NSERC
  6. China Scholarship Council fellowship
  7. Division Of Environmental Biology
  8. Direct For Biological Sciences [1342872] Funding Source: National Science Foundation

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Grasslands play important roles in ecosystem production and support a large farming and grazing industry. An accurate and efficient way is needed to estimate grassland health and production for monitoring and adjusting management to get sustainable products and other ecosystem services. Previous studies of grasslands have shown varying relationships between productivity and biodiversity, with most showing either a positive or a hump-shaped relationship where productivity peaks at intermediate diversity. In this study, we used airborne imaging spectrometry combined with ground sampling and eddy covariance measurements to estimate the spatial pattern of production and biodiversity for two sites of contrasting productivity in a southern Alberta prairie ecosystem. Resulting patterns revealed that more diverse sites generally had greater productivity, supporting the hypothesis of a positive relationship between production and biodiversity for this site. We showed that the addition of evenness to richness (using the Shannon Index of dominant species instead of the number of dominant species alone) improved the correlation with optical diversity, an optically derived metric of biodiversity based on the coefficient of variation in spectral reflectance across space. Similarly, the Shannon Index was better correlated with productivity (estimated via NDVI (Normalized Difference Vegetation Index)) than the number of dominant species alone. Optical diversity provided a potent proxy for other more traditional biodiversity metrics (richness and Shannon index). Coupling field measurements and imaging spectrometry provides a method for assessing grassland productivity and biodiversity at a larger scale than can be sampled from the ground, and allows the integrated analysis of the productivity-biodiversity relationship over large areas.

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