This manuscript presents a rigorous analysis of the multi-scale dynamics of net ecosystem exchange (NEE) and its environmental drivers in the Pantanal, a region undergoing significant anthropogenic pressures from deforestation, agriculture, and the broader impacts of climate change. By leveraging high temporal resolution data, the authors quantitatively explore the interactions between carbon fluxes and environmental variables, contributing valuable insights to ongoing efforts in climate–ecosystem modelling.

The methodological framework is sound and well justified. The authors employ Detrended Cross-Correlation Analysis (DCCA) to investigate the scale-dependent relationships between NEE and key climatic drivers. This approach has been widely used and validated in various contexts, and its application here is both appropriate and effective. The paper is clearly structured, with coherent progression from methods to results and a balanced, thoughtful interpretation. The quality of writing is excellent—precise, fluent, and engaging—making this an enjoyable and informative read. The attention to detail throughout is commendable.

Detrended Cross-Correlation Analysis (DCCA) Findings

The DCCA results reveal a nuanced picture of carbon–climate interactions across temporal scales:

• NEE exhibits weak anti-correlation with both sensible heat flux (H) and latent heat flux (LE) at small scales, suggesting that rapid energy flux variations exert limited short-term control on carbon exchange.
• A moderate anti-correlation with global radiation (Rg) at the daily scale points to complex radiative and physiological dynamics influencing photosynthetic activity.
• Positive correlation with relative humidity (rH) supports the role of humidity in facilitating photosynthetic processes and maintaining canopy conductance.
• Weak anti-correlations with air temperature and soil temperature indicate that temperature fluctuations have a limited direct influence on NEE in this humid ecosystem.
• A moderate anti-correlation with vapor pressure deficit (VPD) at the daily scale reflects the sensitivity of NEE to water stress and evaporative demand.

Conclusions on Carbon Flux–Climate Interactions

The study compellingly demonstrates that carbon flux–climate relationships in the Pantanal are strongly scale-dependent.

• The observed weekly-scale anti-persistence in NEE suggests that ecosystem recovery rhythms play a critical role in regulating carbon balance, underscoring the ecological importance of short-term processes that are often overlooked.
• Daily fluxes are primarily governed by solar radiation and evaporative demand, while seasonal patterns align with the region’s hydrological cycles.
• These insights have meaningful implications for regional climate modelling and ecosystem management, emphasizing the necessity of maintaining natural flooding regimes to support the Pantanal’s carbon regulation capacity.

Overall Assessment

This is a well-executed and insightful study that enhances our understanding of carbon–climate coupling in floodplain ecosystems. The analytical approach is robust, the interpretations are well grounded in the data, and the broader implications are clearly articulated. The findings also open avenues for comparative analyses in drier and semi-arid ecosystems, where water-use efficiency and carbon–water coupling dynamics are more pronounced. Such extensions would be valuable for testing the generality of the patterns identified here.

In conclusion, this manuscript makes a substantial and well-argued contribution to ecosystem and climate science. I commend the authors for their meticulous work and recommend the paper for publication with only minor revisions:

Line 370 – revisit this section as these details have already been provided in lines 357 and 356

It would be great to include a map of the site, and a picture of the site set up as an insert – preferably.

The article entitled “Multi-scale dynamics of carbon dioxide flux and its environmental drivers in the Pantanal wetland” evaluates the temporal variability and interdependence between Net Carbon Exchange in the Ecosystem, using two very well-chosen and widely validated tools in the literature for this type of analysis: autocorrelation, using the DFA method, and cross-correlation, using the ρDCCA coefficient.

Materials and Methodology

I verify that the methodology employed was given adequate treatment. The conditions described in the manuscript are clear and coherent, allowing other researchers to replicate the study without ambiguous interpretations. The description of the DFA methods and the ρDCCA cross-correlation coefficient is written in a clear and mathematically formal manner.

Relation of techniques in preliminary results

i) Table 1 describes the interpretation of the αDFA exponent, referring to five conditions.

The point of attention is related to the values ​​found in the adjustments presented in Table 3.

It is observed that, for the daily verification, in Tair and Tsoil, the αDFA values ​​were 1.51 and 1.55, respectively.

According to the literature, αDFA values ​​close to 1.5 indicate a type of random (Brownian noise) signal, whose variations over time are highly correlated. This differs from a non-stationary signal, whose statistical properties (such as mean, variance, and autocorrelation) vary over time.

The question that arises is:

Wouldn't it be interesting to add the αDFA value for values ​​greater than 1.5 to Table 1 and justify this in the text?

ii) In Table 2, the authors present the interpretation of the ρDCCA coefficient, but describe it in the caption as the DFA exponent. I believe this should be revised.

iii) The same mistake occurs in Table 3. The table shows the calculated αDFA values, but the caption describes it as the interpretation of ρDCCA. I also suggest reviewing this.

iv) I did not identify a clear description of the persistence levels in the text; only the information that values ​​above 0.5 indicate persistent behavior. The text mentions 0.85 as moderate persistence, but to validate this statement, the authors should explain what they consider to be weak, moderate, and strong persistence.

Personally, I believe it would be sufficient to indicate only the term persistence, without the subdivision. I recommend reviewing this point.

Regarding the ρDCCA coefficient

The results presented by the model are clear and consistent; I have no further observations to make regarding this part.

Overall assessment

The proposal presented here is a rigorous and intellectually refined study that significantly contributes to advancing the understanding of carbon-climate interactions in a highly specific and relevant ecosystem.

Regarding the methodology and methods employed, there is soundness and consistency.

I understand that the contributions are relevant and I RECOMMEND the manuscript for publication, with the only caveat being the points mentioned above, which should be improved.