Integrated Analysis of Productivity and Biodiversity in a Southern Alberta Prairie

Abstract

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.

Monitoring Grassland Seasonal Carbon Dynamics, by Integrating MODIS NDVI, Proximal Optical Sampling, and Eddy Covariance Measurements

“…Due to the high variability of the eddy covariance footprint, which varies with wind speed and direction [84], it is not always feasible to directly couple optical and flux footprints, so approximations (e.g., Figure 2) are often necessary. Preliminary results of the flux footprint analysis for our site suggest a typical flux footprint area slightly larger than 1 ha [41]. In our study, the 1 ha grid NDVI 680,800 measurements were intended to approximate the footprint of the eddy covariance tower in size, but not necessarily in shape due to the temporal dynamics of the flux footprint.…”

“…The two sites differed slightly in vegetation cover and microtopography; E5 appeared very flat and uniform, while the E3 landscape varied slightly more than E5 in microtopography and vegetation cover within the flux tower footprint [41], but was still a relatively uniform grassland-dominated site. The sites represent a typical dry mixed grass prairie community as described by Adams et al [9].…”

“…This allowed us to calculate the NDVI 680,800 of an area approximating the flux footprint and to compare the field spectral measurements with those derived from the MODIS satellite sensors. A separate study [41] demonstrated that, due to the uniformity of the landscape, the NDVI values of these different sampling regions were very similar, with an error of 4% or less. In addition to the grid sampling, the field spectrometer was also used to measure spectral reflectance at exactly the same Spectral processing software (Multispec, http://specnet.info) was used to calculate raw reflectance values, calculated as the ratio between upwelling surface radiance (R target ) and downwelling solar irradiance (I downwelling ):…”

“…One band consisted of two PAR sensors (S-LIA, Onset Computer Corporation) that measured the photosynthetic photon flux density (PPFD) within the PAR band (400-700 nm), and the other band consisted of two PYR sensors (S-LIB, Onset Computer Corporation) measuring irradiance or radiance across a spectral range from 300 to 1100 nm. Both up-and down-looking sensors had cosine (nominally 180 degree) foreoptics, allowing us to sample a relatively large area («100 m 2 ) immediately adjacent to the flux tower, but restricted to a small portion of the total flux footprint (typically >1 ha, with variations depending on windspeed and wind direction) [41]. This phenology station provided a continuous, high temporal resolution proxy NDVI by means of continuous broad-band reflectance in both PAR and PYR bands sampled every 1-min during the whole growing season and logged as 15-min averages, thus monitoring seasonal changes in the vegetation photosynthetic phenology [43].…”

“…The rest of the summer usually has lower precipitation, but summer rainfall regimes can vary markedly from year to year, with a similarly variable effect on productivity [12]. The management regime consisted of light, rotational grazing, as further described in Wang et al [41].…”