| 2. |
- Le Noë, Julia, et al.
(författare)
-
Soil organic carbon models need independent time-series validation for reliable prediction
- 2023
-
Ingår i: Communications Earth & Environment. - 2662-4435. ; 4:1
-
Tidskriftsartikel (refereegranskat)abstract
- Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions.
|
|
| 3. |
- Parmentier, Frans Jan W., et al.
(författare)
-
Vulnerability and resilience of the carbon exchange of a subarctic peatland to an extreme winter event
- 2018
-
Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:6
-
Tidskriftsartikel (refereegranskat)abstract
- Extreme winter events that damage vegetation are considered an important climatic cause of arctic browning - a reversal of the greening trend of the region - and possibly reduce the carbon uptake of northern ecosystems. Confirmation of a reduction in CO2 uptake due to winter damage, however, remains elusive due to a lack of flux measurements from affected ecosystems. In this study, we report eddy covariance fluxes of CO2 from a peatland in northern Norway and show that vegetation CO2 uptake was delayed and reduced in the summer of 2014 following an extreme winter event earlier that year. Strong frost in the absence of a protective snow cover - its combined intensity unprecedented in the local climate record - caused severe dieback of the dwarf shrub species Calluna vulgaris and Empetrum nigrum. Similar vegetation damage was reported at the time along ∼1000 km of coastal Norway, showing the widespread impact of this event. Our results indicate that gross primary production (GPP) exhibited a delayed response to temperature following snowmelt. From snowmelt up to the peak of summer, this reduced carbon uptake by 14 (0-24) g C m-2 (∼12% of GPP in that period) - similar to the effect of interannual variations in summer weather. Concurrently, remotely-sensed NDVI dropped to the lowest level in more than a decade. However, bulk photosynthesis was eventually stimulated by the warm and sunny summer, raising total GPP. Species other than the vulnerable shrubs were probably resilient to the extreme winter event. The warm summer also increased ecosystem respiration, which limited net carbon uptake. This study shows that damage from a single extreme winter event can have an ecosystem-wide impact on CO2 uptake, and highlights the importance of including winter-induced shrub damage in terrestrial ecosystem models to accurately predict trends in vegetation productivity and carbon sequestration in the Arctic and sub-Arctic.
|
|
| 4. |
- Qiu, Chunjing, et al.
(författare)
-
ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales
- 2018
-
Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 11:2, s. 497-519
-
Tidskriftsartikel (refereegranskat)abstract
- Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 Combining double low line 0.76; Nash-Sutcliffe modeling efficiency, MEF Combining double low line 0.76) and ecosystem respiration (ER, r2 Combining double low line 0.78, MEF Combining double low line 0.75), with lesser accuracy for latent heat fluxes (LE, r2 Combining double low line 0.42, MEF Combining double low line 0.14) and and net ecosystem CO2 exchange (NEE, r2 Combining double low line 0.38, MEF Combining double low line 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2<0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.
|
|
