Radiation use efficiency of the herbaceous layer of dry Chaco shrublands and woodlands: Spatial and temporal patterns

Abstract

Aims Monitoring rangeland above‐ground net primary production (ANPP) requires information on the variation of radiation use efficiency (RUE). We studied the spatial and temporal variations of RUE of the herbaceous layer (RUEH) in woodlands and shrublands and its association with grazing regime, environmental, and vegetation variables. Location We worked in the Arid Chaco (Argentina), an ecotone region between the Chaco and Monte phytogeographic provinces. Woody and herbaceous species coexist in variable proportions in relation to a regional precipitation gradient and local edaphic variations. Methods and results Over eight growing seasons, we estimated RUEH at 12 sites, each with two contrasting grazing regimes (moderate and severe). To do this, we related estimated ANPPH from biomass harvests and APARH (absorbed photosynthetically active radiation of the herbaceous layer) calculated from the MODIS normalized difference vegetation index (NDVI). Then we linked the RUEH with precipitation, physiognomy, soil, and landscape data. Most of the spatial variability of RUEH was accounted for by the grazing regime. Moderately grazed areas had a three times greater RUEH than severely grazed ones (0.507 and 0.180 g MJ−1 respectively). They also exhibited different proportions of herbaceous functional types. Physiognomic characteristics of the woody layer explained a significant proportion of the spatial variation of RUEH not explained by grazing regime. RUEH was between 30 and 150% greater in woodlands than in shrublands depending on whether the sites were under moderate or severe grazing respectively. Conclusion Grazing regime and woody physiognomy accounted for most of the variation in herbaceous radiation use efficiency. Our results show that RUEH may be predicted with greater accuracy from a combination of vegetation maps and information on grazing regime. Thus, our models could be incorporated into web platforms that provide ANPPH (forage) monitoring services based on satellite data, in order to improve their estimates in woodlands, shrublands and savanna ecosystems.

Review of Remote Sensing Applications in Grassland Monitoring

“…The results demonstrated that precipitation and temperature were the first and second most important variables, while nitrogen deposition also had a significant impact. The results in [84] also demonstrated that the temporal variability of NPP could be largely explained by the precipitation during growing seasons. Many others studies have also pointed out that precipitation and temperature directly affect the distribution and accumulation of primary production [48,75,79,82,92,94].…”

“…Zheng et al [76] also constructed a CASA model, which estimated FPAR based on the NDVI and proved a strong correlation between spring phenology and NPP in alpine grasslands. In addition, the NDVI time series were built by Blanco et al [84] using MODIS data to estimate FPAR by a linear model, and NPP was calculated by a LUE method. Gaffney et al [85] constructed the NDVI time series with high spatial and temporal resolution by fusing Landsat and MODIS data to fit the APAR for semiarid rangelands, and the above-ground NPP was estimated by a linear model similar to Equation (1).…”