Leakage Effects from Reforestation: Estimating the Impact of Agricultural Displacement for Carbon Markets
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsAn interesting article, presenting a multi-faceted approach to assessing land afforestation in the Amazon. The manuscript has a correct and typical structure of research papers. The introduction is well written, but there are no references to policies, strategies and regulations, i.e. current regulations and laws regarding land turnover, nature and forest protection, afforestation policy and CO2 sequestration. Therefore, it is difficult to assess the contribution that this research can make. The introduction needs to be expanded, also to present research by other authors in this field. There is a lack of information on the need and justification for undertaking this study.
Please add: What is the practical significance of this study? and what does it contribute to science? What new does this study bring to the research already conducted in this area?
Please elaborate and provide more information on Verra and ART-TREES? How do these assumptions relate to the research?
A presentation of the legal framework would be a valuable addition to the introductory chapter. It is recommended to prepare a subsection on the legal framework for land use and regulation of CO2 absorption. Please provide more information on afforestation projects and the size of economic incentives for landowners (?).
Please write why the methods used were chosen for the analyses? Why were these and not other methods of research and solving the research problem chosen?
Please supplement the research methodology with a description of the variables that were taken into account in the model. Why can the variables (listed in Table 1) be related to the research problem and affect the solution of the research problem? I have doubts about the validity of using these specific variables? Please explain why these and not other variables (included in Table 1) were included?. The theoretical framework needs to be expanded, based on the literature. The research methodology does not contain detailed references to the data sources - websites, source databases? - used in the analyses (please specify exactly from which sources the data (indicators) were collected for the analyses).
The conclusions are presented too generally, please be more specific. The conclusions should refer to the research questions posed. The conclusions should not repeat the results and statements presented in the earlier parts of the manuscript. They should include more practice recommendations.
The English could be improved to more clearly express the research
Author Response
We thank Reviewer 1 for their feedback and constructive suggestions, which have helped us refine and clarify the manuscript. Below, we address each point raised – which resonates with our writing revisions.
Comment: "The introduction is well written, but there are no references to policies, strategies and regulations... It is difficult to assess the contribution that this research can make."
Response: We appreciate the reviewer’s observation and have revised the introduction and mostly the background to include a policy-oriented framing. We now reference relevant Brazilian regulations such as the Forest Code, the National Policy on Climate Change (PNMC), and programs such as the Low-Carbon Agriculture Plan (ABC+). We also discuss global frameworks including NDCs under the Paris Agreement and voluntary carbon markets, which provide incentives for afforestation and reforestation. This context enhances the relevance of our study for both national and international climate governance.
Comment: "The introduction needs to be expanded to present research by other authors in this field..."
Response: We have added references to recent and foundational studies on reforestation, leakage effects, and land-use change modeling (e.g., Lambin & Meyfroidt, 2011; Busch et al., 2019; West et al., 2020). This situates our contribution within the academic literature and theoretical framing of Land System Science. Still, we reiterate that leakage analysis is in its infancy (as pointed by some papers), and one of our justifications for this study is the existence of a few science-based analyses for a growing topic in climate policy and private investments for carbon sequestration.
Comment: "There is a lack of information on the need and justification for undertaking this study."
Response: We have rewritten parts of the introduction to explicitly state the knowledge gap our study addresses: the lack of empirical evidence on spatial leakage from reforestation projects. While leakage has been widely studied in REDD+ contexts, the specific dynamics of reforestation-driven land competition are understudied. This impacts how real-world reforestation carbon projects account for leakage (if accounting for it), mostly within voluntary markets. Our study provides empirical estimates using a spatial Durbin model to quantify these effects and offer insights directly applicable to carbon market protocols (e.g. carbon credits from reforestation projects).
Comment: "Please add: What is the practical significance of this study? And what does it contribute to science?"
Response: We now emphasize the practical implications of our findings for carbon credit verification systems (e.g., Verra, ART-TREES), land-use zoning, and incentive design. Scientifically, the study contributes by applying a rigorous spatial econometric approach to a novel domain—reforestation leakage—using high-resolution, long-term panel data.
Comment: "Please elaborate and provide more information on Verra and ART-TREES. How do these assumptions relate to the research?"
Response: We agree with this argument and have added it to the introduction/background, as well as expanded the discussion to explain that current carbon credit standards often assume fixed or simplistic leakage buffers (e.g., Verra’s baseline leakage assumptions, ART-TREES’ regional adjustment factors). We argue that current protocols and assumptions may be insufficient and that spatially explicit modeling is needed to avoid overestimating carbon sequestration.
Comment: "A presentation of the legal framework would be a valuable addition..."
Response: We agree and have created a new subsection in the background to outline the key regulations and economic incentive that influence afforestation and land use in Brazil, including the Brazilian Forest Law, credit incentives to reforestation, and NDCs. The discussion section also depicts how carbon market intersecting with legal instruments.
Comment: "Please write why the methods used were chosen..."
Response: We have clarified those spatial econometric methods—particularly the Spatial Durbin Model—were chosen because they allow us to estimate both direct and indirect (spillover) effects across municipalities. These models are ideal for evaluating land-use dynamics influenced by neighboring activities, and they address issues of spatial autocorrelation that conventional statistical models may overlook. Moreover, this modeling is the traditional approach to address economic causalities of land change, within the theoretical framework of science.
Comment: "Please supplement the research methodology with a description of the variables... Why can the variables (Table 1) be related to the research problem...?"
Response: We have revised the methods section and expanded the explanatory notes to Table 1, linking each variable to a theoretical or empirical rationale – as we mentioned, some are just controls for underlying causes, while other variables are proximate causes as defined in the literature (See: Geist & Lambin 2022, Proximate Causes and Underlying Driving Forces of Tropical Deforestation). For example, land rent captures the opportunity cost of land use, stocking rate proxies for intensification potential, and enforcement data reflects institutional constraints on deforestation. Citations and justifications have been revised accordingly.
Comment: "The research methodology does not contain detailed references to the data sources – websites, databases..."
Response: That’s correct – and we’re sorry for that. We have added specific references and URLs for each data source previously mentioned (e.g., MapBiomas platform, IBGE SIDRA database, ERA5 climate reanalysis, CHIRPS precipitation). This ensures full transparency and reproducibility of the data inputs.
Comment: "The conclusions are presented too generally... They should include more practice recommendations."
Response: We have rewritten the conclusions to directly respond to the original research questions and summarize the key empirical findings. In addition, we now include specific policy recommendations such as integrating spatial leakage modeling into carbon accounting methodologies and improving the design of afforestation incentives to avoid indirect deforestation.
Comment: "The English could be improved to more clearly express the research."
Response: We have carefully revised the manuscript for clarity. Minor grammatical errors and awkward phrasing were corrected, and sentence structures were polished to ensure a more professional and readable presentation.
Reviewer 2 Report
Comments and Suggestions for AuthorsComments and Suggestions for Authors of the study: Leakage effects from reforestation: estimating the impact of agricultural displacement for carbon markets
- Some data of correlations about the results of the Spatial Panel Regression estimating the impact of forest plantation expansion on vegetation loss, and about the sensitivity analysis of spatial Spillovers Across Different Distances are important to show in the abstract.
- Is possible the inclusion of some hypothesis?
- In the introduction section is important to include the objectives in the last paragraph and to avoid the description of results in this section.
- I surgency is the addition in the introduction section of background about the other methods similar to used in this study (advantage and disadvantage).
- Lines 80-86, and lines 101-102, are necessary some references.
- Is necessary a justification about the period (2000-2023) used for evaluation of deforestation leakage caused by forest plantation.
- Is there some references or justification for the variables employed in table 1?
- Is important that the formulas 3 and 4 include some references
- The results are well presented with clear figures and tables. However, the discussion sometimes lacks depth. Suggestion: Deepen the discussion by linking your findings to specific data detected in other studies with different methods
- In the methods, maybe a scheme about the methodological processes will be more interesting for the clarity of the steps used for the investigations.
Author Response
We thank Reviewer 2 for the constructive and straightforward insightful comments, which have helped us improve the clarity and contextual depth of the manuscript. See below our response to each point – which resonates with our writing revisions.
Comment 1: "Some data of correlations about the results of the Spatial Panel Regression estimating the impact of forest plantation expansion on vegetation loss, and about the sensitivity analysis of spatial Spillovers Across Different Distances are important to show in the abstract."
Response: Alright! We revised the abstract to include key quantitative results from the spatial panel regression, such as the magnitude and significance of the estimated leakage effects and the sensitivity of results to distance decay specifications. We understand this provides a clearer summary of the empirical findings upfront.
Comment 2: "Is possible the inclusion of some hypothesis?"
Response: Sure thing! We derivate two formal hypotheses from the research questions in paragraph #4, in order to guide the analysis:
- H1: Forest plantation expansion is associated with increased vegetation loss in neighboring municipalities (deforestation leakage).
- H2: Livestock intensification moderates the relationship between forest plantation expansion and vegetation loss. These hypotheses now appear at the end of the introduction to guide the empirical testing.
Comment 3: "In the introduction section it is important to include the objectives in the last paragraph and to avoid the description of results in this section."
Response: We understand it, and agree with a revised introduction accordingly. We split paragraph 4 into two and clearly state the objectives that were originally there – then, move results to their section. Indeed, your suggestion makes it easier to polish the intro into a tight, theory-driven entry point. The previous structure mimics big policy journals where it is common to briefly mention key results in the last paragraph of the introduction – not to interpret or detail them, but to orient the reader.
Comment 4: "I suggest the addition in the introduction section of background about the other methods similar to those used in this study (advantages and disadvantages)."
Response: We appreciate this suggestion and have expanded the background and methods to include a brief review of related empirical approaches, such as difference-in-differences for leakage studies (a great example is the recent paper of Moffette & Gibbs, 2021 – “Agricultural Displacement and Deforestation Leakage in the Brazilian Legal Amazon”). We have clarified those spatial econometric methods—particularly the Spatial Durbin Model—were chosen because they allow us to estimate both direct and indirect (spillover) effects across municipalities. These models are ideal for evaluating land-use dynamics influenced by neighboring activities, and they address issues of spatial autocorrelation that conventional statistical models may overlook. Moreover, this modeling is the traditional approach to address economic causalities of land change, within the theoretical framework of science.
Comment 5: "Lines 80–86, and lines 101–102, are necessary some references."
Response: Agreed. We have added recent references in these sections.
Comment 6: "Is necessary a justification about the period (2000–2023) used for evaluation of deforestation leakage caused by forest plantation."
Response: This timeframe is due to (i) data availability, and (ii) the occurrence of reforestation projects in the land cover dataset. Therefore, we clarified in the methods section that the 2000–2023 window allows us to capture both early reforestation dynamics and the more recent boom in carbon-offset driven reforestation efforts. This time frame provides a long-term perspective on spatial land-use dynamics and the cumulative effects of plantation expansion.
Comment 7: "Is there some references or justification for the variables employed in Table 1?"
Response: We have revised the methods section and expanded the explanatory notes to Table 1, linking each variable to a theoretical or empirical rationale – as we mentioned, some are just controls for underlying causes, while other variables are proximate causes as defined in the literature (See: Geist & Lambin 2022, Proximate Causes and Underlying Driving Forces of Tropical Deforestation). For example, land rent captures the opportunity cost of land use, stocking rate proxies for intensification potential, and enforcement data reflects institutional constraints on deforestation. Citations and justifications have been revised accordingly.
Comment 8: "It is important that the formulas 3 and 4 include some references."
Response: Of course! Marginal effects (equation 4) are quite usual in the econometric analysis, so we included the proper citations. Also, Eq. 4 derives from Eq. 1, which already cites Bellemare & Wichman (2020), and Norton (2022) – therefore, we bring these citations to the paragraph about Eq. 4. For Eq. 3, we revised for rephrasing where formulas 3 appears, because the cited study of Richards et al (2014) uses a similar approach to indirect land use change with soy.
Comment 9: "The results are well presented with clear figures and tables. However, the discussion sometimes lacks depth. Suggestion: Deepen the discussion by linking your findings to specific data detected in other studies with different methods."
Response: Thank you for this suggestion – we consider it extremely useful for this and future work. Thus, we revised the discussion to include comparative interpretations with other studies using alternative approaches to study leakage and indirect land-use change, such as the recent paper of Moffette & Gibbs (2021). This will help to position our findings within the broader literature and strengthen the relevance of our results.
Comment 10: "In the methods, maybe a scheme about the methodological processes will be more interesting for the clarity of the steps used for the investigations."
Response: We agree and have added a schematic figure to the methods section.
We thank Reviewer 2 again for these valuable suggestions.
Reviewer 3 Report
Comments and Suggestions for AuthorsTraditional reforestation has a low survival rate due to the more recurrent periods of drought, so it is currently no longer considered a real solution to mitigate the effects of climate change.
This information should go in the results section or in discussion
The methodology needs to be described as to what type of satellite images were used to determine the change in land use and vegetation between the periods 2000 and 2023, image resolution, kappa index, atmospheric correction of the images, software used, etc.
How was the reforested area estimated? The survival of the reforestations was verified in the field, and what was the sampling design to determine the reforestations and plantations?
The report adds:
1. What is the main question addressed by the research?
The research proposes an analysis of the effect that deforestation has on the reduction of forests that store carbon dioxide, thus affecting the carbon credit market.
2. What parts do you consider original or relevant to the field? What
specific gap in the field does the paper address?
The article raises an original aspect by making a correlation between the loss of forest ecosystems, main causes and restoration scenarios through reforestation and commercial plantations that contribute to carbon capture, however, it is limited to a statistical analysis of information generated by other sources, without generating a multitemporal analysis process of satellite images and field information on the success or failure of reforestation.
3. What does it add to the subject area compared with other published
material?
Add a multivariate analysis with aspects related to the loss of forest cover, meteorological variables (precipitation and temperature) and social variables such as population growth and how this affects the carbon credit market.
4. What specific improvements should the authors consider regarding the
methodology?
It is necessary to generate your own multi-temporal analysis to estimate land use and vegetation changes, as well as to collect field information on the survival of reforestation and plantations, as well as an estimate of the tons of carbon captured by reference ecosystems.
5. Are the conclusions consistent with the evidence and arguments presented?
Were all the main questions posed addressed? By which specific experiments?
Las conclusiones se basan en sus estimaciones, sin embargo, carecen de información de campo que respalde sus resultados, debido a que solo se basan en información disponible de otras fuentes, por lo tanto, es necesario puntos de control en campo que respalden los resultados presentados.
6. Are the references appropriate?
They present adequate bibliographic information
7. Any additional comments on the tables and figures and the quality of the
data.
There is a lack of plans and graphs that would facilitate a better interpretation of the results.
Comments for author File: 
Comments.pdf
Author Response
We are grateful for the thoughtful comments provided by Reviewer 3. Below, we respond point-by-point to each observation, aiming to clarify the study's focus, methodological approach, and its contributions within the appropriate scientific framing.
Comment: "Traditional reforestation has a low survival rate due to the more recurrent periods of drought, so it is currently no longer considered a real solution to mitigate the effects of climate change."
Response: We respectfully disagree with the generalized conclusion that reforestation is "no longer considered a real solution." While challenges such as seedling mortality and drought-induced stress are well documented (e.g., Brancalion et al., 2022), reforestation remains a central pillar of nature-based solutions in both policy and science. Multiple peer-reviewed syntheses (Griscom et al., 2017; Cook-Patton et al., 2020) reaffirm the viability and cost-effectiveness of reforestation as a climate mitigation strategy. Rather than dismissing reforestation, our study seeks to evaluate a key limitation—namely, deforestation leakage—which may undermine its net benefit. We have clarified this framing in the discussion.
As stated by other authors (Lennox et al., 2018; Heinrich et al.,2021), both conservation and restoration are mandatory strategies for enhancing terrestrial carbon sinks. In the context of our paper, Brazil is the sixth largest emitter of GHGs, and its primary source of emissions is deforestation (SEEG, 2022), mainly in the Amazon. For this reason, conserving forests remains one of the most critical allies in climate mitigation, as they are essential carbon sinks, particularly in the context of Nature-based solutions (NbS). Additionally, reforestation, a key NbS, offers one of the most significant potentials for economic climate change mitigation, while also preserving biodiversity and maintaining other ecosystem services, along with the protection and enhancement of secondary vegetation (Crouzeilles et al., 2020; Griscom et al., 2020; Lewis et al., 2019; Pugh et al., 2019; Mitchard, 2018; Watson et al., 2018; IPCC, 2022) – we added the relevant citations in the paper to be checked.
Comment: "The methodology needs to be described as to what type of satellite images were used to determine the change in land use and vegetation between the periods 2000 and 2023, image resolution, kappa index, atmospheric correction of the images, software used, etc."
Response: We appreciate this suggestion and have expanded our data description to clarify that we rely on land cover datasets provided by MapBiomas (also published by Souza et al 2020, in a paper in the MDPI journal Remote Sensing), an internationally recognized consortium that processes and validates satellite imagery (Landsat, 30m resolution) using Google Earth Engine and machine learning classifiers. MapBiomas products are publicly available for different countries in LatAm and Asia, and they report classification accuracy and confusion matrices, typically with overall accuracy above 85%. As our analysis is grounded in spatial econometrics rather than remote sensing techniques, we use these pre-processed datasets as inputs, rather than generating our own image classifications.
Comment: "How was the reforested area estimated? The survival of the reforestations was verified in the field, and what was the sampling design to determine the reforestations and plantations?"
Response: We clarify that reforestation in our study is proxied by the "forest plantation" class in the MapBiomas land cover database. This class captures large-scale commercial and restoration plantations and is validated by the MapBiomas team through classification protocols. While field verification of survival rates is important, our study operates at the municipality level and focuses on spatial spillover effects, rather than plantation success or biomass accumulation. The sampling design is thus spatial-econometric, not ecological. We have revised the background section to clarify this scale and disciplinary focus.
Comment 2: "What parts do you consider original or relevant to the field?... limited to statistical analysis..."
Response: We appreciate the recognition of the study’s originality in linking afforestation to potential displacement effects using spatial models. While the study does not perform new land classification or field-based survival assessment, its originality lies in the application of spatial Durbin panel models to analyze leakage effects over two decades using harmonized, high-resolution land use data – therefore, we do generate a multitemporal analysis in the panel data regression approach. This allows for a unique empirical contribution to the literature on indirect land use change and carbon offset reliability.
Comment 3: "What does it add to the subject area..."
Response: We agree with the reviewer’s summary and highlight that the study integrates climatic, economic, and policy-related variables to better understand the drivers of deforestation leakage. This adds depth to existing research that often examines these drivers in isolation.
Comment 4: "It is necessary to generate your own multi-temporal analysis..."
Response: While we understand the value of generating primary spatial data and conducting fieldwork, the scope of our research is aligned with policy evaluation using existing validated datasets and spatial econometrics. Many other studies do not rely on generating their own data or remote sensing dataset – e.g. Moffette & Gibbs (2021), Richards et al (2014). Furthermore, generating field-based data on reforestation survival or estimating site-specific carbon sequestration would be valuable extensions, but they fall outside the analytical scope and scale of this study. We have acknowledged this limitation explicitly in the discussion.
Although the analysis is based on secondary data, the modeling approach rigorously controls for time trends, spatial dependence, and municipal characteristics to isolate the effects of forest plantation expansion – similar to what we see in the cited literature, e.g. Moffette & Gibbs (2021), Richards et al (2014), and others. While field validation is ideal, the strength of our approach lies in offering large-scale empirical insights on spatial dynamics that are difficult to capture through field-based sampling alone.
Comment 7: "There is a lack of plans and graphs..."
Response: We agree and have added new figures in the revised manuscript.
Round 2
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript lacks graphs and plans that allow observing changes in land use and vegetation.
Comments for author File: Comments.pdf
Author Response
We thank the reviewer for this valuable suggestion. To address this comment and enhance the spatial interpretation of our findings, we have added a new figure in the results (see Figure 3 now) that visualizes land-use changes and model-derived spillover effects across the Brazilian Amazon from 2000 to 2023. These maps complement the statistical results and provide an intuitive understanding of where and how reforestation-induced displacement may be occurring. The visualizations reinforce our argument that spatial spillovers are not diffuse or random, but instead follow identifiable geographic and economic patterns. This new figure has been placed at the end of the Results section, just before the Discussion, to support our interpretation of the empirical findings.
Round 3
Reviewer 3 Report
Comments and Suggestions for Authorsthe manuscript has been sufficiently improved to warrant publication in Land
