Abstract
This study investigated the potential to predict primary production in benthic ecosystems using meteorological variables and spectral indices. In situ production experiments were carried out during the vegetation season of 2020, wherein the primary production and spectral reflectance of different communities of submerged aquatic vegetation (SAV) were measured and chlorophyll (Chl a+b) concentration was quantified in the laboratory. The reflectance of SAV was measured both in air and underwater. First, in situ reflectance spectra of each SAV class were used to calculate different spectral indices, and then the indices were correlated with Chl a+b. Indices using red and blue band combinations such as 650/450 and 650/480 nm explained the largest part of variability in Chl a+b for datasets measured in air and underwater. Subsequently, the best-performing indices were used in boosted regression trees (BRT) models, together with meteorological data to predict the community photosynthesis of different SAV classes. The predictive power (R2) of production models were very high, estimated at the range of 0.82–0.87. The variable contributing the most to the model description was SAV class, followed in most cases by the water temperature. Nevertheless, the inclusion of spectral indices significantly improved BRT models, often by over 20%, and surprisingly their contribution mostly exceeded that of photosynthetically active radiation.
Highlights
Academic Editor: Vona MéléderPrimary production is a backbone of life on earth and is a key aspect of the global carbon cycle [1,2]
Our results showed that indices that use near infrared (NIR) wavelength as reference were the most sensitive to variations in Chl a+b in the case when vegetation spectra were measured in air
The objective of the current study was to develop spectral indices for the production assessment of benthic vegetation using in situ spectral reflectance data and to test those indices together with other environmental variables (SAV class, temperature, photosynthetically active radiation (PAR)) in productivity models
Summary
Academic Editor: Vona MéléderPrimary production is a backbone of life on earth and is a key aspect of the global carbon cycle [1,2]. Primary production is traditionally mapped in situ using biochemically based techniques, e.g., quantifying changes in oxygen concentration within a sealed environment, incorporation of inorganic carbon into organic matter, or fluorescence kinetics [3]. These techniques yield very precise estimates of primary production for the studied locations and times, the methods are not practically feasible for large-scale studies. Due to the above-mentioned reasons and the lack of standardized large-scale methods to map the primary production of seascapes, photosynthetic processes are currently among the most important targets of the remote sensing science
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