Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

Abstract

The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with process-based vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average, well simulated but too homogeneous among vegetation types when compared with field estimates using forest inventory data.

Dynamics in carbon exchange fluxes for a grazed semi-arid savanna ecosystem in West Africa

“…Possible explanations for the high CO 2 fluxes are a high fraction of C4 species, alleviated water stress conditions, and a strong grazing pressure that results in compensatory growth and fertilization effects. In areas of broadly similar climate, several factors can influences the fluxes, such as solar irradiance, species composition, anthropogenic factors, cultivation, fire sequences, disturbances, soil type, nutrient variability and age of the vegetation (Semmartin and Oesterheld, 1996;Rockström and de Rouw, 1997;Tagesson et al, 2009;Hutley and Beringer, 2011;Vourlitis and Ribeiro da Rocha, 2011).…”

Examining forest net primary productivity dynamics and driving forces in northeastern China during 1982–2010

“…estimated the NPP dynamic from 1982 to 1999 based on normalized difference vegetation index (NDVI) and detected seasonal dynamics of terrestrial NPP in response to climatic changes in China. Based on remote sensing datasets, numerous related studies were also conducted to simulate NPP values and applied to different regions with a number of models (Tagesson et al, 2009;Yu et al, 2009b;Huang et al, 2010).…”

Microplastics and hydrocarbons in soils: Quantification as an anthropic carbon source

“…We estimated annual net primary productivity (NPP) using the Monteith (1972) model: $$${NPP}=\int {PAR}\times {fPAR}\times \varepsilon ,$$$where PAR is the photosynthetic active radiation (PAR; MJ), fPAR is the fraction of radiation absorbed by vegetation, and ε is the radiation use efficiency (mass C or dry mass per MJ). The fPAR can be derived from spectral indices, such as the normalized difference vegetation index (NDVI; Paruelo et al, 1997) or leaf area index (LAI; Tagesson et al, 2009). We utilized three different approaches for the fPAR parameter: (1) fPAR product generated from satellite remote sensing, (2) from the linear function of NDVI, and (3) coupled to LAI by the Beer–Lambert law (see Supporting Information).…”