Nutrient and stoichiometric time series measurements of decomposing coarse detritus in freshwaters

Ecology. 2023 Aug;104(8):e4114. doi: 10.1002/ecy.4114. Epub 2023 Jun 15.

Abstract

Decomposition of coarse detritus (e.g., dead organic matter larger than ~1 mm such as leaf litter or animal carcasses) in freshwater ecosystems is well described in terms of mass loss, particularly as rates that compress mass loss into one number (e.g., a first-order decay coefficient, or breakdown rate, "k"); less described are temporal changes in the elemental composition of these materials during decomposition, with important implications for elemental cycling from microbes to ecosystems. This stands in contrast with work in the terrestrial realm, where a focus on detrital elemental cycling has provided a sharper mechanistic understanding of decomposition, especially with specific processes such as immobilization and mineralization. Notably, freshwater ecologists often measure carbon (C), nitrogen (N), and phosphorus (P), and their stoichiometric ratios in decomposing coarse materials, including carcasses, wood, leaf litter, and more, but these measurements remain piecemeal. These detrital nutrients are measurements of the entire detrital-microbial complex and are integrative of numerous processes, especially nutrient immobilization and mineralization, and associated microbial growth and death. Thus, data relevant to an elemental, mechanistically focused decomposition ecology are available in freshwaters, but have not been fully applied to that purpose. We synthesized published detrital nutrient and stoichiometry measurements at a global scale, yielding 4038 observations comprising 810 decomposition time series (i.e., measurements within a defined cohort of decomposing material through time) to build a basis for understanding the temporality of elemental content in freshwater detritus. Specifically, the dataset focuses on temporally and ontogenetically (mass loss) explicit measurements of N, P, and stoichiometry (C:N, C:P, N:P). We also collected ancillary data, including detrital characteristics (e.g., species, lignin content), water physiochemistry, geographic location, incubation system type, and methodological variables (e.g., bag mesh size). These measurements are important to unlocking mechanistic insights into detrital ontogeny (the temporal trajectory of decomposing materials) that can provide a deeper understanding of heterotroph-driven C and nutrient cycling in freshwaters. Moreover, these data can help to bridge aquatic and terrestrial decomposition ecology, across plant or animal origin. By focusing on temporal trajectories of elements, this dataset facilitates cross-ecosystem comparisons of fundamental decomposition controls on elemental fluxes. It provides a strong starting point (e.g., via modeling efforts) for comparing processes such as immobilization and mineralization that are understudied in freshwaters. Time series from decomposing leaf litter, particularly in streams, are common in the dataset, but we also synthesized ontogenies of animal-based detritus, which tend to decompose rapidly compared with plant-based detritus that contains high concentrations of structural compounds such as lignin and cellulose. Although animal-based data were rare, comprising only three time series, their inclusion in this dataset underscores the opportunities to develop an understanding of decomposition that encompasses all detrital types, from carrion to leaf litter. There are no copyright or proprietary restrictions on the dataset; please cite this data paper when reusing these materials.

Keywords: breakdown; detrital-microbial system; lake; mesocosm; necromass; plant residue; pond; resource stoichiometry; river; stream.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Carbon / analysis
  • Ecosystem*
  • Fresh Water
  • Humans
  • Lignin* / analysis
  • Lignin* / metabolism
  • Nitrogen / analysis
  • Plant Leaves / chemistry
  • Plants / metabolism
  • Time Factors

Substances

  • Lignin
  • Carbon
  • Nitrogen