This file is from the Long-term Carbon and Nitrogen, and Phosphorus Dynamics of Leaf and Fine Root Litter project (LIDET-Long-term Intersite Decomposition Experiment Team). This file contains only the Arctic LTER data. In particular the mass looses over the ten year study. Three types of fine roots (graminoid, hardwood, and conifer), six types of leaf litter (which ranged in lignin/nitrogen ratio from 5 to 75), and wooden dowels were used for litter incubations over a ten year period.
Data Set Results
The Changing Seasonality of Artic Stream Systems (CSASN) was active from 2010 to 2012. The CSASN goal was to quantify the relative influences of throughflow, lateral inputs, and hyporheic regeneration on the seasonal fluxes C, N, and P in an arctic river network, and to determine how these influences might shift under seasonal conditions that are likely to be substantially different in the future. There were a number of TASCC and Plateau nutrient additions at each sampling location.
The Changing Seasonality of Arctic Stream Systems (CSASN) was active from 2010 to 2012. The CSASN goal was to quantify the relative influences of through flow, lateral inputs, and hyporheic regeneration on the seasonal fluxes C, N, and P in an arctic river network, and to determine how these influences might shift under seasonal conditions that are likely to be substantially different in the future. There were a number of TASCC and Plateau nutrient additions at each sampling location.
The Changing Seasonality of Arctic Stream Systems (CSASN) was active from 2010 to 2012. The CSASN goal was to quantify the relative influences of through flow, lateral inputs, and hyporheic regeneration on the seasonal fluxes C, N, and P in an arctic river network, and to determine how these influences might shift under seasonal conditions that are likely to be substantially different in the future. There were a number of tracer addition for spiraling curve characterization (TASCC) and Plateau nutrient additions at each sampling location.
A study investigating the mechanisms that control long-term response of tussock tundra to fire and to increases in air temperature, CO2, nitrogen deposition and phosphorus weathering. The MBL MEL was used to simulate the recovery of three types of tussock tundra, unburned, moderately burned, and severely burned in response to changes in climate and nutrient additions. The simulations indicate that the recovery of nutrients lost during wildfire is difficult under a warming climate because warming increases nutrient cycles and subsequently leaching within the ecosystem.
Two Figaro TGS 2600 sensors were installed at the Toolik Wet Sedge site in late June 2012 to 2018.
Files used to generate the data for figures in:
Rastetter, EB, Kling, GW, Shaver, GR, Crump, BC, Gough, L. Ecosystem Recovery from Disturbance Is Constrained by N Cycle Openness, Vegetation-Soil N Distribution, Form of N Losses, and the Balance between Vegetation and Soil-Microbial Processes. Ecosystems (2020). https://doi.org/10.1007/s10021-020-00542-3.
We use the Multiple Element Limitation (MEL) model to examine the responses of twelve ecosystems - from the arctic to the tropics and from grasslands to forests - to elevated carbon dioxide (CO2), warming, and 20% decreases or increases in annual precipitation.
We use the Multiple Element Limitation (MEL) model to examine the responses of twelve ecosystems - from the arctic to the tropics and from grasslands to forests - to elevated carbon dioxide (CO2), warming, and 20% decreases or increases in annual precipitation.
Climate change is increasing extreme weather events, but effects on high-frequency weather variability and the resultant impacts on ecosystem function are poorly understood. We assessed ecosystem responses of arctic tundra to changes in day-to-day weather variability using a biogeochemical model and stochastic simulations of daily temperature, precipitation, and light. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates.
Climate change is increasing extreme weather events, but effects on high-frequency weather variability and the resultant impacts on ecosystem function are poorly understood. We assessed ecosystem responses of arctic tundra to changes in day-to-day weather variability using a biogeochemical model and stochastic simulations of daily temperature, precipitation, and light. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates.