Comparison of remote sensing and plant trait-based modelling to predict ecosystem services in subalpine grasslands

摘要: There is a growing demand for spatially explicit assessment of multiple ecosystem services (ES) and remote sensing (RS) can provide valuable data to meet this challenge. In study, located in the Central French Alps, we used high spatial spectral resolution RS images assess ES based on underpinning properties (EP) subalpine grasslands. We estimated five EP (green biomass, litter mass, crude protein content, species diversity soil carbon content) from using empirical methods maps were calculated as simple linear combinations EP. Additionally, RS-based results compared with plant trait-based statistical modelling approach that predicted land use, abiotic trait (modelling approach). The comparison between approaches showed provided better insight into fine-grained distribution thereby ES, whereas reflected use signal underpinned models agreement two at 20-m varied 16 22% individual EP, but total service supply it was only 7%. Furthermore, identified alpine grazed meadows class areas values (hot spots) mown-grazed permanent low few (cold spots). Whereas hot spots small subset those by approach, cold rather scattered, patches limited overlap results. Despite limitations associated timing campaigns field requirements, offers continuous mapping thus proxies ES. Although applied area one type ecosystem, believe broader availability fidelity airborne satellite will promote larger other ecosystems.