Abstract
Plant functional groups—in our case grass, herbs, and legumes—and their spatial distribution can provide information on key ecosystem functions such as species richness, nitrogen fixation, and erosion control. Knowledge about the spatial distribution of plant functional groups provides valuable information for grassland management. This study described and mapped the distribution of grass, herb, and legume coverage of the subalpine grassland in the high-mountain Kazbegi region, Greater Caucasus, Georgia. To test the applicability of new sensors, we compared the predictive power of simulated hyperspectral canopy reflectance, simulated multispectral reflectance, simulated vegetation indices, and topographic variables for modeling plant functional groups. The tested grassland showed characteristic differences in species richness; in grass, herb, and legume coverage; and in connected structural properties such as yield. Grass (Hordeum brevisubulatum) was dominant in biomass-rich hay meadows. Herb-rich grassland featured the highest species richness and evenness, whereas legume-rich grassland was accompanied by a high coverage of open soil and showed dominance of a single species, Astragalus captiosus. The best model fits were achieved with a combination of reflectance, vegetation indices, and topographic variables as predictors. Random forest models for grass, herb, and legume coverage explained 36%, 25%, and 37% of the respective variance, and their root mean square errors varied between 12–15%. Hyperspectral and multispectral reflectance as predictors resulted in similar models. Because multispectral data are more easily available and often have a higher spatial resolution, we suggest using multispectral parameters enhanced by vegetation indices and topographic parameters for modeling grass, herb, and legume coverage. However, overall model fits were merely moderate, and further testing, including stronger gradients and the addition of shortwave infrared wavelengths, is needed.
Highlights
Worldwide, high-mountain grasslands are species-rich habitats that include numerous endemic species (Ko€rner 2004) but are commonly highly affected by natural and land use-triggered erosion, land degradation, and land use changes
This study described and mapped the distribution of grass, herb, and legume coverage of the subalpine grassland in the high-mountain Kazbegi region, Greater Caucasus, Georgia
To test the applicability of new sensors, we compared the predictive power of simulated hyperspectral canopy reflectance, simulated multispectral reflectance, simulated vegetation indices, and topographic variables for modeling plant functional groups
Summary
High-mountain grasslands are species-rich habitats that include numerous endemic species (Ko€rner 2004) but are commonly highly affected by natural and land use-triggered erosion, land degradation, and land use changes (eg Tasser and Tappeiner 2002; Lehnert et al 2014; Wiesmair et al 2016). The high species richness of subalpine to alpine grasslands results from, and is affected by, long-term agricultural use. Traditional high-mountain land use systems with low input of system-specific organic fertilizers had greatly contributed to a distinct floristic pattern. This changed when mineral fertilizers and more effective agricultural techniques were introduced, making more intensive management regimes applicable to large grassland sites while modifying the traditional mowing and grazing regimes, as well as homogenizing floristic patterns (Homburger and Hofer 2012). The introduction of mineral nitrogen and phosphorus fertilizers caused the greatest change in the floristic composition of grassland and resulted in an increased abundance of ubiquitous species (Bu€hler and Roth 2011)
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