A retrospective analysis of scientific publications on the deep sea from 1987 to 2016.

The deep sea remains the least known biome. Despite this fact, anthropic activities have affected these regions in various ways. The objective of this study was to outline the scientific production scenario based on deep sea research and to analyze trends present in the literature.

Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints.

We conducted an inverse modeling analysis, using a variety of data streams (tower-based eddy covariance measurements of net ecosystem exchange, NEE, of CO2, chamber-based measurements of soil respiration, and ancillary ecological measurements of leaf area index, litterfall, and woody biomass increment) to estimate parameters and initial carbon (C) stocks of a simple forest C-cycle model, DALEC, using Monte Carlo procedures. Our study site is the spruce-dominated Howland Forest AmeriFlux site, in central Maine, USA. Our analysis focuses on: (1) full characterization of data uncertainties, and treatment of these uncertainties in the parameter estimation; (2) evaluation of how combinations of different data streams influence posterior parameter distributions and model uncertainties; and (3) comparison of model performance (in terms of both predicted fluxes and pool dynamics) during a 4-year calibration period (1997-2000) and a 4-year validation period ("forward run", 2001-2004).