| 1. |
- Harper, Anna B., et al.
(författare)
-
Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
- 2021
-
Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 14:6, s. 3269-3294
-
Tidskriftsartikel (refereegranskat)abstract
- Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the "soil14_psi" experiments), when the critical threshold value for inducing soil moisture stress was reduced ("soil14_p0"), and when plants were able to access soil moisture in deeper soil layers ("soil14_dr&z.ast;2"). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.
|
|
| 2. |
- Peralta-Maraver, Ignacio, et al.
(författare)
-
The riverine bioreactor : An integrative perspective on biological decomposition of organic matter across riverine habitats
- 2021
-
Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 772
-
Forskningsöversikt (refereegranskat)abstract
- Riverine ecosystems can be conceptualized as 'bioreactors' (the riverine bioreactor) which retain and decompose a wide range of organic substrates. The metabolic performance of the riverine bioreactor is linked to their community structure, the efficiency of energy transfer along food chains, and complex interactions among biotic and abiotic environmental factors. However, our understanding of the mechanistic functioning and capacity of the riverine bioreactor remains limited. We review the state of knowledge and outline major gaps in the understanding of biotic drivers of organic matter decomposition processes that occur in riverine ecosystems, across habitats, temporal dimensions, and latitudes influenced by climate change. We propose a novel, integrative analytical perspective to assess and predict decomposition processes in riverine ecosystems. We then use this model to analyse data to demonstrate that the size-spectra of a community can be used to predict decomposition rates by analysing an illustrative dataset. This modelling methodology allows comparison of the riverine bioreactors performance across habitats and at a global scale. Our integrative analytical approach can be applied to advance understanding of the functioning and efficiency of the riverine bioreactor as hotspots of metabolic activity. Application of insights gained from such analyses could inform the development of strategies that promote the functioning of the riverine bioreactor across global ecosystems.
|
|
