Sediment texture influences extracellular enzyme activity and stoichiometry across vegetated and non-vegetated coastal ecosystems

Author:

Wei Mengjie1,Lundquist Carolyn2,Schwendenmann Luitgard1ORCID

Affiliation:

1. The University of Auckland School of Environment

2. NIWA: National Institute of Water and Atmospheric Research

Abstract

Abstract The conversion of organic matter by extracellular enzymes can reveal important insights into carbon processing and nutrient cycling. The activity and stoichiometry of hydrolytic extracellular enzymes were investigated to assess the effects of sediment texture on microbially-mediated decomposition in coastal ecosystems. Enzyme activity was quantified across transects from vegetated (mangrove) to non-vegetated (tidal flat) habitats in two New Zealand coastal ecosystems that vary in sediment texture (sandy: Hobson Bay, muddy: Snells Beach). The activity of five key hydrolyzing enzymes involved in organic matter processing and nutrient cycling were determined: 1) β-glucosidase (hydrolysis of cellulose to glucose); 2) β-N-acetylglucosaminidase (catalyzes the terminal reaction in chitin degradation); 3) alkaline phosphatase (releases soluble inorganic phosphate groups from organophosphates); 4) β-D-cellobiohydrolase (hydrolyzes cellulose to generate cellobiose); and 5) β-xylosidase (catalyzes hemicellulose degradation). All enzymes had higher activity at the muddy site but enzyme activities in these coastal habitats were generally lower than has been reported for terrestrial, freshwater, and other estuarine ecosystems. Extracellular enzyme activities (EEA) did not differ between habitats at the sandy site, whereas EEA was lower in the non-vegetated habitats for some enzymes at the muddy site. Enzyme stoichiometric ratios showed that most habitats at both muddy and sandy sites were predominately C and P limited. These results can be used to advance our understanding of the biogeochemical processes underpinning the response of coastal ecosystems to land-derived nutrient and sediment inputs.

Publisher

Research Square Platform LLC

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