Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO₂ and a Gradient of Experimental Warming

Abstract

The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon fluxes are no longer a clear guide in the Anthropocene. However, carbon‐flux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting flux‐ versus pool‐based carbon cycle variables and (2) the time points when temperature and CO2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting workflow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data‐model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C flux‐related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool‐related response variables. Given the uncertainties in forecasting carbon fluxes and pools, our analysis showed that statistically different responses of fast‐turnover pools to various CO2 and warming treatments were observed sooner than slow‐turnover pools. Our study has identified the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future.

Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models

“…Code availability. The EcoPAD (v1.0) portal is available at https: //ecolab.nau.edu/ecopad_portal/ (Jiang et al, 2019a), and code is provided at the GitHub repository (https://github.com/ou-ecolab, Jiang et al, 2019b).…”

“…Relevant data for this paper are available at the SPRUCE project web page (https://mnspruce.ornl.gov/, last access: January 2019) and the EcoPAD (v1.0) web portal (https://ecolab. nau.edu/ecopad_portal/, Jiang et al, 2019a). Additional data can be requested from the corresponding author.…”

Photosynthetic and Respiratory Responses of Two Bog Shrub Species to Whole Ecosystem Warming and Elevated CO2 at the Boreal-Temperate Ecotone

“…Future research on the role of leaf structure, nutrients and photosynthate transport and utilization is needed to understand whole-plant responses to these treatments and thus predict ecosystem response to novel environments. Through the combined efforts of intensive measurement campaigns and integrative modeling efforts (e.g., Jiang et al, 2018;Jensen et al, 2019), it may be possible to capture the responses of individual species to this novel long-term field manipulation and build better predictions of ecosystem response to global change in this critical ecotone between the boreal and temperate regions.…”

Realized ecological forecast through interactive Ecological Platform for Assimilating Data into model (EcoPAD)

“…The impact of 738 external forcing is especially obvious in short term carbon flux predictions. Forcing uncertainty 739 resulted in higher forecasting uncertainty in carbon flux compared to that from parameter 740 uncertainty [Jiang et al, 2018]. Mismatches in forecasted vs. realized forcing greatly increased 741 simulated GPP and the discrepancy diminished in the long run.…”