Key drivers of the annual carbon budget of biocrusts from various climatic zones determined with a mechanistic data-driven model
Abstract. Biocrusts are a worldwide phenomenon, contributing substantially to ecosystem functioning. Their growth and survival depend on multiple environmental factors, including climatic conditions. While the physiological responses of biocrusts to individual environmental factors have been examined in laboratory experiments, the relative importance of these factors along climatic gradients is largely unknown. Moreover, it is not fully understood how acclimation of biocrusts may alter the relative impacts of certain factors. We aim here at determining the relative effects of environmental factors on biocrusts along climatic gradients, using the carbon balance of biocrust organisms as a measure of their performance. Additionally, we explore the role that seasonal acclimation plays in the carbon balance of biocrusts. We applied a data-driven mechanistic model at six study sites along a climatic gradient to simulate the annual carbon balance of biocrusts dominated by different lichen and moss species. Furthermore, we performed several sensitivity analyses to investigate the relative importance of driving factors, thereby including the impacts of acclimation. Our modeling approach suggests substantial effects of light intensity and relative humidity in temperate regions, while air temperature has the strongest impact at alpine sites. In drylands, ambient CO2 concentration and also the amount of rainfall are important drivers of the carbon balance of biocrusts. Seasonal acclimation is a key feature, mostly in temperate regions, affecting biocrust functioning. We conclude that climate change, which may lead to warmer and, in some regions, drier air, will potentially have large effects on long-term carbon balances of biocrusts at global scale. Moreover, we highlight the key role of seasonal acclimation, which suggests that the season and timing of collecting and monitoring biocrusts should be given additional consideration in experimental investigations, especially when measurements are used as the basis for quantitative estimates and forecasts.
Yunyao Ma et al.
Yunyao Ma et al.
Yunyao Ma et al.
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Ma and others model the carbon balance of biocrusts at multiple sites with differing climatic conditions. The results provide interesting context for understanding biocrust physiology worldwide but the presentation needs work for simplicity and clarity.
Abstract: more quantitative if possible. This extends to the introduction starting especially on line 50 where the text could benefit from numeric values to help the reader understand the magnitude of C stocks and fluxes that biocrusts interact with.
Regarding 69: when environmental conditions are in an optimal range vascular plant would usually be favored, so what constitutes ‘optimal’ for biocrusts here?
92: ‘a Q10 relationship’
Regarding longwave radiation, I question somewhat the use of the ERA5 data if avoidable; were local surface temperature data available at any of the sites and if so how closely do these data align with the ERA5 data?
Reading on to 127, if surface temperature are available, avoiding ERA5 in the model would be advisable. Line 127 should be in the previous section.
On line 174, something more than a visual comparison is necessary. In Fig. 1 a-d (should be b-e because the left panel should be a), the consistent early peak in the simulated temperatures should be corrected for if possible because the heat capacity that entered the model is obviously incorrect. I’m not sure how this interacts with the discussion 188 if temperature was approximated. When is the temperature approximated and when was it modeled? Section 2.3.2 needs improvement also on line 204 regarding the negative photosynthesis rate. This could be a negative net C flux or the Rd parameter exceeding carbon uptake, but photosynthesis itself isn’t negative.
I’m not entirely convinced about the usefulness of section 2.5 and its description was rather meandering. That being said Fig. 6a is interesting but I wish that the normalization was done differently as a normalized value of < - 10 (for the case of air temperature) is difficult to discern.
How does the data driven model in 2.3 differ from LiBry in 2.6 especially given that LiBry doesn’t fit the observations well as described in 3.2? Was there an effort to improve LiBry given the results of the study?
362: not the moisture required to give them the ability to be active?
The Fig. 7 legend could use more detail. I had to search what the “fixed” and “dynamic” parameters meant. They were detailed in section 2.5, where these terms could have been more clearly defined.
422 and elsewhere: subscripting (here in CO_2) is inconsistent, used correctly here but not in other places.
For precipitation, how is dewfall and other factors that are important to biocrusts considered? In 477 and elsewhere, is vapor pressure deficit not a more physiologically consistent approach for estimating stomatal function than relative humidity and/or is relative humidity mostly a surrogate for the surface being sufficiently wet for biocrust function to proceed?
569 and elsewhere: wasn’t there just one alpine site such that a more accurate summary would be “at an alpine site”?
570: “obvious” is subjective.