The impacts of Payment for Ecosystem Services programmes on health and wellbeing: a systematic review protocol

Payment for Ecosystem Services, Payment for Environmental Services, Market-based Environmental Policies, Environmental Conservation Policies, Health, Subjective Wellbeing, Co-benefits, Systematic Review, Protocol, Carbon Offset. ALL Metrics - Views Downloads How to cite this article Calderon M, Campbell M, Kopasker D et al. The impacts of Payment for Ecosystem Services programmes on health and wellbeing: a systematic review protocol [version 1; peer review: 1 approved]. NIHR Open Res 2025, 5:55 (https://doi.org/10.3310/nihropenres.13928.1) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente Select a format first ▬ ✚ Study Protocol [version 1; peer review: 1 approved] Micaela Calderon https://orcid.org/0009-0001-4840-8406 1, Mhairi Campbell https://orcid.org/0000-0002-4416-7270 1, Daniel Kopasker1, [...] Mercy J. Borbor-Cordova2, Valerie Wells https://orcid.org/0000-0002-7283-6208 1, Claire Niedzwiedz https://orcid.org/0000-0001-6133-4168 3, Batul Rojeab Bravo https://orcid.org/0000-0001-9318-0319 4, J. Firmino de Sousa Filho https://orcid.org/0000-0001-5057-385X 5,6, Philip Broadbent1, Jonathan R Olsen https://orcid.org/0000-0002-5356-8615 1, S Vittal Katikireddi1Micaela Calderon https://orcid.org/0009-0001-4840-8406 1, Mhairi Campbell https://orcid.org/0000-0002-4416-7270 1, [...] Daniel Kopasker1, Mercy J. Borbor-Cordova2, Valerie Wells https://orcid.org/0000-0002-7283-6208 1, Claire Niedzwiedz https://orcid.org/0000-0001-6133-4168 3, Batul Rojeab Bravo https://orcid.org/0000-0001-9318-0319 4, J. Firmino de Sousa Filho https://orcid.org/0000-0001-5057-385X 5,6, Philip Broadbent1, Jonathan R Olsen https://orcid.org/0000-0002-5356-8615 1, S Vittal Katikireddi1 PUBLISHED 03 Jul 2025 Author details Author details 1 MRC/CSO Social and Public Health Science Unit, Clarice Pears Building 90 Byres Road, University of Glasgow, Glasgow, G12 8TB, Scotland, UK 2 Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, E C090112, Ecuador 3 School of Health and Wellbeing, Clarice Pears Building 90 Byres Road, University of Glasgow, Glasgow G12 8TB, UK 4 City St George's, University of London, London, England, SW17 0RE, UK 5 Research Department, Center for Data and Knowledge Integration for Health, Salvador, Bahia, 40045060, Brazil 6 School of Economics, Federal University of Bahia, Salvador, Bahia, 40045060, Brazil 2 Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, E C090112, Ecuador 3 School of Health and Wellbeing, Clarice Pears Building 90 Byres Road, University of Glasgow, Glasgow G12 8TB, UK 4 City St George's, University of London, London, England, SW17 0RE, UK 5 Research Department, Center for Data and Knowledge Integration for Health, Salvador, Bahia, 40045060, Brazil 6 School of Economics, Federal University of Bahia, Salvador, Bahia, 40045060, Brazil Micaela Calderon Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Mhairi Campbell Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Daniel Kopasker Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Mercy J. Borbor-Cordova Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Valerie Wells Roles: Methodology, Resources, Software, Writing – Review & Editing Roles: Methodology, Resources, Software, Writing – Review & Editing Claire Niedzwiedz Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Batul Rojeab Bravo Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing J. Firmino de Sousa Filho Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Philip Broadbent Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Jonathan R Olsen Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing S Vittal Katikireddi Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Software, Writing – Review & Editing Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Software, Writing – Review & Editing OPEN PEER REVIEW REVIEWER STATUS Payment for Ecosystem Services (PES) programmes are being implemented worldwide to encourage the maintenance of sustainable and healthy ecosystems, with some of them part of the carbon offsetting market and carbon capture strategies developed to reduce carbon emissions. However, their impacts on health, health inequalities and wellbeing remain unclear. This systematic review aims to assess the health and subjective wellbeing impacts on individuals/communities who are incentivised to protect their environments. We will search the databases EconLit, Medline, CAB Abstracts® and Global Health® via Web of Science, GreenFILE, International Initiative for Impact Evaluation (3ie) and grey literature from World Health Organisation (WHO), Food and Agriculture Organisation (FAO), and World Bank. Studies will be eligible for inclusion if they are assessing PES, a health or subjective WB outcome, and have a comparator group (including different levels of the intervention). Abstracts and full text articles will be assessed independently by two researchers. Risk of bias will be assessed using ROBINS-I for quantitative studies and CASP for qualitative studies. For quantitative data we will do random-effects meta-analysis to estimate pooled effect sizes where possible. For the qualitative data we will report people’s experiences of PES and potential mechanisms through which health impacts arise using content analysis. Effect heterogeneity across differing forms of implementation, sociodemographic characteristics and contexts will be explored. We will refine our provisional logic model to incorporate insights from the quantitative and qualitative data. Certainty of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. This review will provide the first synthesis of the health and subjective wellbeing impacts of PES programmes, helping to understand the potential for market-based policies to achieve environmental and health co-benefits. We anticipate reporting findings in peer-reviewed publications, conference presentations and through briefings to policymakers and community leaders. Many governments have implemented various environmental conservation policies aimed at reducing human actions on environmental degradation. Among these policies, Payment for Ecosystem Services (PES) programmes have gained increasing popularity to encourage the maintenance of sustainable and healthy ecosystems and some of them are part of the carbon offsetting market. Previous studies suggest that these policies have a significant impact on reducing environmental degradation. However, there is limited evidence regarding the impact of these types of policies on the health and wellbeing of the PES providers and on the wider community. This paper describes planned research for a comprehensive assessment of what is already known from all of the previously published relevant research – referred to as a ‘systematic review’. We want to bring together the findings of previous evaluations of the impacts of PES programmes on health and wellbeing. To make the results more reliable, the review will follow a structured approach, with at least two people working on most stages to double check each other’s work. We will search for articles discussing the impacts of PES programmes on the health and/or wellbeing on people who receive money through PES programmes or the wider community in which they live. Specific criteria will be used to determine which studies to include and exclude. We will summarise this information to analyse the impacts of PES programmes on health and subjective wellbeing. This information will help to understand the potential for these payment-based approaches to achieve environmental and health and wellbeing co-benefits. Payment for Ecosystem Services, Payment for Environmental Services, Market-based Environmental Policies, Environmental Conservation Policies, Health, Subjective Wellbeing, Co-benefits, Systematic Review, Protocol, Carbon Offset. Corresponding Author(s) Micaela Calderon ([email protected]) Grant information: This project is funded by the National Institute for Health and Care Research (NIHR) under its Grant Reference Number NIHR134801. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. MCalderon, BRB, FF, MJB are funded by NIHR (NIHR134801). MC is funded by Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). JRO is funded by Medical Research Council (MC_UU_00022/) and Chief Scientist Office (SPHSU19). SVK and DK are funded by Medical Research Council (MC_UU_00022/2), European Research Council (949582), and Scottish Government Chief Scientist Office (SPHSU17). PB is funded by Wellcome Funded PhD at School of Health and Wellbeing, University of Glasgow (304823-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2025 Calderon M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Calderon M, Campbell M, Kopasker D et al. The impacts of Payment for Ecosystem Services programmes on health and wellbeing: a systematic review protocol [version 1; peer review: 1 approved]. NIHR Open Res 2025, 5:55 (https://doi.org/10.3310/nihropenres.13928.1) First published: 03 Jul 2025, 5:55 (https://doi.org/10.3310/nihropenres.13928.1) Latest published: 03 Jul 2025, 5:55 (https://doi.org/10.3310/nihropenres.13928.1) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Ecosystems and human health are intrinsically interlinked1. Nature provides services and goods that are fundamental for health, such as food, clean air and water, as well as more complex services that ensure longer-term population health, like preventing floods, land degradation, collectively referred to as “ecosystem services (ES)”1–3. Conversely, environmental degradation can have myriad diverse effects on human health, increasing the risk of food insecurity, acute and chronic diseases, and harm the mental wellbeing of populations1,4–6. From an economics perspective, the consequences of environmental deterioration reflect not only an overuse and exploitation of natural resources, but also a historical failure to properly put an economic value on the positive externalities that people are receiving from ES1,7. In response, policymakers and governments have increasingly been promoting market-based policies, programmes, and plans to offset human actions that have a negative impact on nature and address environmental degradation8,9, putting a monetary value to ES that were previously unpriced, and, in doing so, valuing the benefits derived from ES7,10. Among these interventions, Payment for Ecosystem Services (PES) programmes have gained popularity, and are being implemented worldwide for their potential to improve environmental conservation, enhance sustainable land use practices, and contribute to poverty alleviation11–15, with an estimated $36-42 billion spent on them in 201816,17. While various definitions of PES exist, we will adopt Wunder’s 2015 definition14: “voluntarily transactions, between service users and service providers that are conditional on agreed rules of natural resource management for generating offsite services”14. In practice, PES often involves transferring money from those who ultimately benefit from ecosystem services (buyers/users) to the people who maintain the provision of these services (PES providers/sellers/participants). PES programmes can be theorised as complex interventions18 and their effects are likely to vary depending on the characteristics of the PES programme itself, the context in which it is implemented, and which people receive it19–22. The main components and characteristics of PES are related to: type of ecosystem service that the programme wants to conserve, payment structures, financing schemes, contract length, whom to pay (individuals, communities), type of payment (cash or in-kind), conditions for receiving the payment, amount of the payment, timing of payments, scale of the PES programme (local, national, regional), actors involved in the programme (public or private sector), type of compliance monitoring, and types of sanctions for non-compliance10,14,19,23–27. Additionally, the source of funding for programmes should be considered which could involve public money or other sources such as carbon offsets and similar schemes28,29. From a purely environmental perspective, PES programmes seem promising as they may have improved forest cover and reduced deforestation rates, although the quality of evidence is low30. However, the health implications of PES remain unclear. While improving ecosystems is itself likely to be beneficial for longer-term human health, it is possible that the health of vulnerable providers of ecosystem services could be adversely impacted. For example, Blundo-Canto et al. discuss in their review, focused on the impacts of PES programmes on livelihoods, that cases in which access rules and land-use restrictions led to segregation between powerful groups and less influential farmers, consequently decreasing community integration30. Le et al. also discuss that PES programmes may also aggravate conflicts (especially when marked social disparities already exist) and highlight that land use changes due to deforestation and poorly defined land use rights have resulted in precarious and vulnerable livelihoods for people that rely on forests31. Furthermore, evidence suggests that the impacts of PES programmes on health and wellbeing may vary by population subgroup, including socioeconomic position, disabilities, gender, level of education, ethnicity, and governance structure of the communities), as well as the characteristics of the payment schemes such as transaction costs, types of schemes, and payment mechanisms10,20,25,32,33. For instance, Brownson et al. showed that PES providers who advocate for reforestation, instead of only receiving cash payments, experience improved health and wellbeing34. A meta-analysis of PES in developing countries indicated that PES programmes have a positive impact on livelihoods (total income, total consumption expenditure and/or gross value of household assets), especially when PES payments are given partly in the form of communal infrastructure, the amount of payment is higher (cash or in-kind) or the transaction costs are lower35. Hejnowicz et al. highlight the importance of how the programmes are constructed and design to achieve effectiveness, efficiency, and equity trade-offs36. No previous systematic reviews of PES have assessed impacts on health or subjective wellbeing in a comprehensive manner, with existing reviews limited to specific population groups or health outcomes, such as children with malaria and diarrhoea disease30,37,38. In this review we will assess health (encompassing physical and mental health) and subjective wellbeing39,40, with outcomes including but not limited to happiness, life satisfaction, quality of life, respiratory diseases, health-related behaviours, depression, anxiety, suicide, maternal and child mortality/morbidity, malnutrition, among others12,34,41. The aim of this systematic review is therefore to assess the impacts of PES programmes on health and subjective wellbeing of both PES participants (individuals and communities) who are incentivised to protect their environments and on the wider community providing the ecosystem. We anticipate this evidence will help understand the potential implications of market-based policies of this type. Logic models can increase the transparency and utility of systematic reviews, highlighting aspects of complex problems that might otherwise be overlooked42–44. The following model was developed based on scoping the relevant literature and feedback from community leaders that are participating in a Payment for Ecosystem programme in Ecuador (Socio Bosque and Socio Manglar), to illustrate the hypothesised causal relationships between PES programmes and health and subjective wellbeing outcomes. While it is well-documented that PES programmes primarily affect environmental outcomes through changes in environment-related behaviours30,37, our logic model focuses on the effects of this programme on health and subjective wellbeing. We plan to refine the logic model in light of the findings from the systematic review. As illustrated in Figure 1, PES programmes are introduced with the primary goal of environmental conservation. However, a number of intermediate outcomes and effects on health and subjective wellbeing are likely to arise due to mechanisms related to increase economic material resources and positive environmental externalities. We hypothesise two groups of mechanisms through which PES programmes can affect health and subjective wellbeing: the behavioural mechanism, material resource mechanism, and the environmental mechanism through spillover effects or positive externalities of the programme. 1. Behavioural mechanism The behavioural mechanism operates through influencing the actions and decisions of individuals and communities in the context of environmental conservation45, with four potential pathways to health and subjective wellbeing. The first pathway is related to changes in environmental behaviours, such as reducing harmful environmental practices for the conservation of the environment and its ES30. This is connected to health and subjective wellbeing through the services that these ecosystems provide. For example, forest conservation improves air quality through the provisioning service that acts via carbon sequestration in the air, resulting in cleaner air, which could affect health by reducing chronic respiratory diseases such as asthma or vector-borne diseases e.g., malaria. Another example could be related to the impact that conservation activities may have on the perceptions of the importance of caring for nature and the acquisition of new environmentally friendly skills. These impacts may lead to changes in the use of less harmful pesticides that can have an impact on diseases like cancer, or an improvement in self-esteem and social capital through networking within the community members. In contrast, replacing other uses of the land may provide lower economic gains46, and therefore can negatively impact people's income that could have an adverse consequence on their health and wellbeing, e.g., less income reduces access to food and may impact on the food security of individuals and communities. Another harmful effect can be linked to the sense of obligation that PES programmes can have, which could generate a negative psychological impact on PES providers because they may feel they are losing control of decisions about their lands and community. The second pathway is related to the impacts PES can have on the composition of the communities. PPI informed us that in some places the programme has increased rates of out-migration within the population in their communities. These changes can lead to loss of social support structure that will have an impact on mental health outcomes. The third pathway incorporates PPI’s perspectives regarding how policy related activities such as monitoring activities in mangroves or native forests is perceived as a dangerous activity due to several threats of violence that participants of the programme are receiving from people that want to do some environmental harmful activities such as logging. This pathway can have a potential effect on all-cause of mortality and an increase in violence rates. The fourth pathway is related to changes in health-related behaviours, which are also linked to the material resource mechanism. Extensive research has shown the association between low income and poorer health and subjective wellbeing outcomes, such as an increase in cardiovascular diseases, malnutrition (undernutrition/obesity), anxiety, depression, limited access to healthcare, reduced life satisfaction, and lower happiness among others47–53. Conversely, studies have also indicated that policies incorporating financial incentives can lead to positive behavioural changes, particularly in health-related behaviours such as healthier eating habits or increases in physical activity54,55. In the case of PES programmes, these health-related behaviours could, for example, be related to an increase in physical activity due to conservation activities, thereby reducing cardiovascular diseases, as well as changes in dietary habits linked to an increase in individual/family income that may impact health outcomes related to malnutrition. Furthermore, this mechanism may shepherd a reduction in stress and anxiety through the feeling of calmness or happiness due to contact with nature56. However, is important to highlight that from the leader’s perspectives some conservation activities such as monitoring activities could be dangerous and may put at risk their lives and health. 2. Material resources mechanism This mechanism may affect health as a result of increasing the income of PES providers and/or affecting health-related behaviours. The latter was already described in the paragraph above. In this section we will only describe how the material resource can be a mechanism itself. For example, payments made to individuals can increase the acquisition of food that could have an impact on maternal and child health outcomes such as undernutrition or obesity, as well as providing a material resource would increase providers' income, alleviating situations such as the financial stress of not having a fixed monthly income, which would conduct to an impact on mental health. Payments at the individual or community level could expand the use of healthcare services through improvements in the community infrastructure. However, poor management of the payments or a lack of consensus of how the payments should be distributed can lead to an increase in conflicts and violence within communities or can lead to an increase in alcohol consumption due to the stress that technicians and managers of the payments may experience. Additionally, it is important to consider that material resources may also cause some other negative effects on health and subjective wellbeing. For example, having more economic capital allows the purchase of more productive assets, which can involve either expanding or intensifying agricultural production from existing land or renting more land. This can lead to the diminishing of other ES, producing a negative impact on health/subjective wellbeing outcomes associated with the provision of these services. 3. Environmental mechanism The indirect environmental mechanism of PES interventions is related to the conservation of ecosystem services14. This mechanism could bring indirect benefits or spillover effects on health and subjective wellbeing for both individuals participating in the programme and those who are not, by safeguarding ecosystems that provide regulating, cultural, provisioning, and supporting services. This can potentially reduce diseases associated with the loss of these services23. For instance, a reduction in water and air pollution may impact respiratory and infectious diseases within these communities. Finally, we highlight two essential points regarding possible variations in health and subjective wellbeing outcomes. Firstly, the importance of considering that health outcomes could vary over time. For example, diseases like cancer may require a long-term perspective to observe any changes as the progression from initial exposure to detectable cancer can span a lengthy period. In contrast short-term outcomes have shorter causal pathways, such as a decrease in maternal and child mortality rates as a result of the provision of healthcare services, that could be observed following a shorter lag period. This will allow us to infer that, although changes in health outcomes like cancer may not be directly observed, it does not mean these changes do not occur, but rather that the time needed to evaluate them might need to be longer. Secondly, it is expected that the effects of PES on health and subjective wellbeing are likely to be heterogenous, and may be influenced by various moderating factors such as participant characteristics (gender, age, socioeconomic position, ethnicity, level of education, forest management governance, disabilities), contextual factors (socioeconomic context, political context, previous ecosystem conditions, geographic location, land ownership, community governance structures), and the specific characteristics of the programme30. For instance, many PES programmes require landowners who wish to participate voluntarily in the programme, but often the people living within areas that provide ES do not have legal ownership of these lands, leaving them excluded from the programmes. This can cause health inequalities by reducing access to material resources for the poorest areas, leading to the health of those in greatest need falling further behind. The systematic review aims to evaluate the positive and negative impacts of PES interventions on health and subjective wellbeing outcomes for both recipients and the wider community. Drawing upon the logic model, the review will be framed around the following research questions: What are the impacts of Payment for Ecosystem Services programmes on health and wellbeing outcomes for recipients and the wider community? Do the impacts of Payment for Ecosystem Services programmes on health and subjective wellbeing outcomes differ according to: a) PES characteristics b) Participant characteristics c) Contextual characteristics How can the logic model describing the mechanisms through which impacts occur be refined considering the evidence from this systematic review? Leaders of three Ecuadorian communities (Quilotoa, Puerto del Morro and Kichwa Rukullakta) involved in a Payment for Ecosystem Programme (Socio Bosque and Socio Manglar) were aided the development of the logic model. They contributed via online meetings and provided feedback following their experiences and community to identify the most suitable primary health outcomes. This information was used to refine the logic model presented in this protocol. Leaders did not participate elsewhere in the study design. The PECOS criteria are described as following and are summarized in Table A1. Population The population of interest includes individuals, communities and/or households living in areas that are providing ecosystem services and those residing in an area where the PES programme is active but did not directly take part in the programme. We will include studies of programmes in all countries. Outcomes for both adults and children will be included in the review and communities will be defined as a group of individuals who share elements of residence that characterise a population. It could include geographical proximity and living in areas that are providing ecosystem services. The communities can be at local, regional or national level. Exposure The exposure (intervention) of interest is defined by Wunder. S as “voluntary transactions, between service users and service providers that are conditional on agreed rules of natural resource management for generating offsite services”14. PES programmes can vary according to their components e.g., type of ecosystem service that the programme wants to conserve, payment structures, financing schemes, contract length, whom to pay, payment duration, type of payment, conditions to receive the payment, amount of the payment, time to pay, scale of the PES scheme, who the actors involved in the programme are, type of compliance monitoring compliance, and types of sanctions for non-compliance10,14,19,23–27. Payments can be directed to individuals, households, communities, or organizations and may be contingent on meeting specific environmental commitments, such as maintaining a certain level of forest cover, or they may be issued in advance of the PES programme. We will not exclude programmes based on any variation in the type of PES programme implemented. However, we will not be assessing the impacts of the money raising element on people who pay for PES e.g. money being collected from payers for carbon offsets. Comparison The comparison group will consist of other similar areas or people where the intervention did not occur, were exposed to a different intervention, or were exposed to differing forms of PES implementation, including: differing intensity, e.g. lower doses of payments; payment duration, e.g. long-term duration; type of payment (cash or in-kind); who received the payment (e.g. individuals or communities); who is the funder/ implementer (private versus public for example); or status of land (private land or state-owned/ protected land). Those residing in an area where the PES programme is active but did not directly take part in the programme. Studies that include a temporal (e.g. before-after) comparison will also be included. Outcome(s) and prioritisation We will include studies that assess the impact of PES programmes on health and subjective wellbeing outcomes as defined below. Outcome measures will include any measure which can be interpreted as a direct measure of health or subjective wellbeing. Studies which only report health service use outcomes will be included. There will be no minimum follow-up period to assess health effects. In the case where synthesis across more than one study is possible, the outcomes from the most similar time point across the studies will be prioritised. For the primary outcomes this protocol will be looking for the outcomes most likely to impact health and subjective wellbeing and are likely to have data available1,6,45,56–66. Specific outcomes could include any of the following: self-reported health measures, maternal and child health outcomes, external causes of morbidity and mortality e.g. violence, alcohol and drug harms, mental health outcomes, healthcare use, all-cause of mortality. All other outcomes will be considered secondary outcomes e.g., infectious diseases, asthma, malnutrition, cancer. Study design and characteristics Study design(s): We will include randomised and non-randomised quantitative studies, including any non-randomised study design (e.g., case-control, observational, or natural experiment studies), qualitative studies, and mixed methods studies. Years: We will conduct the search strategy from 1990 until the present period. This date is justified since the first implementation of PES as a policy tool was in 1990, as noted in previous systematic reviews.30. Language: English, Spanish, and Portuguese. Publication status: Peer-reviewed publications and relevant grey literature reporting primary research from World Health Organisation (WHO), Food and Agriculture Organisation of the United Nations (FAO), World Bank will be searched to identify publication using the same keywords as were used in the database searches. Exclusion criteria 1. Incorrect population: 2. Incorrect intervention scheme: Studies that are not evaluating a PES conservation programme. Studies that focus on assessing the impacts on people from whom money is raised. 3. Incorrect outcome: 4. Incorrect study type: Systematic reviews, meta-analysis, other types of reviews, correspondence, essays or opinion articles without original data will be excluded. The citations of systematic reviews and other structured reviews will be checked following completion of the search to ensure inclusion of any appropriate studies not already captured. Articles that only have abstracts and where full access to the article is not possible. 5. Incorrect language: The following databases will be systematically searched: EconLit, Medline, CAB Abstracts® and Global Health® via Web of Science, GreenFILE, International Initiative for Impact Evaluation (3ie). In addition, grey literature from World Health Organisation (WHO), Food and Agriculture Organisation (FAO), and World Bank will be searched to identify publication using the same keywords as were used in the database searches. The terms and search strategy are listed in the Table A2, where we illustrate a search strategy example in CAB Abstracts® and Global Health® via Web of Science. The strategy and set of terms used will be modified as needed for each database.

lists and citations of the included studies as well as relevant systematic reviews identified during the search will also be reviewed to identity additional pertinent studies. The search strategy will not be restricted by factors such as age, gender, language, or race. We will conduct the search strategy from 1990 until the present period. This date is justified since the first implementation of PES as a policy tool was in 1990, as noted in previous systematic reviews30. Selection of studies Covidence will be used to manage the search results. MCalderon, as the lead reviewer, along with a second reviewer, will independently assess each study at all stages. Initially, the screening will focus on titles and abstracts, with only those studies meeting the inclusion criteria moving forward to full-text review. Studies whose titles and abstracts clearly do not fit the inclusion criteria will be excluded at this stage. During the full-text screening phase only studies which fully meet the inclusion criteria will be selected to progress to data extraction. Where there is disagreement or ambiguity about inclusion the full reference will be obtained to allow further scrutiny of the eligibility of the study. The reasons for exclusion will be documented in Covidence and reported according to the PRISMA guidelines67. In cases where included articles report duplicate data, the decision on which data to include will be based on the study design (prioritising lower risk of bias), sample size, directness in relation to the review question and ability to standardise effect estimates for the synthesis. Conflicts in any part of the study selection and selection process will be discussed with a third independent reviewer or expert. The review team will hold regular meetings to discuss and interpret the evidence. Endnote X9 will be used as a reference library for the review. During the search and screening Covidence will be used to manage records and Excel spreadsheets will be used for data extraction. Data extraction will be performed by the lead reviewer (MCalderon) and independently checked by a second reviewer. To ensure consistency across reviewers, prior to beginning we will pilot the data extraction process with all who are involved in the data extraction process, extracting data from ~3 diverse studies and comparing results. We will resolve disagreements within the data extracted by discussion and in consultation with a third member of the research team when necessary. Data extraction process Data extraction will be carried out by the lead reviewer, MCalderon, and independently verified by a second reviewer. Considering the heterogeneity of the study designs and outcomes included within the scope of this review, both quantitative and qualitative data will be extracted using a convergent segregate approach. This approach involves separately synthesising quantitative and qualitative data leading to generate separate evidence, which will be then integrated68. Data will be extracted on an Excel spreadsheet. Any disagreements between reviewers will be resolved through discussion or by consulting a third reviewer. If relevant data appear to be collected but are insufficiently reported for data extraction, the study investigators will be contacted to obtain the necessary information. We will extract specific details about populations, study methods, PES components, and outcome data relevant to the review objective. For the qualitative studies we will extract will specifically details about population, context, geographical location, study design, methods, PES components and self-reported health perceptions of interest participants’ reported health and wellbeing-related experiences of PES relevant to the review objective, as well as any potential mechanism through PES may impact on health and wellbeing. Data extracted will include all the data items described in detail in Table A3. Two reviewers will independently assess risk of bias for all studies with disagreements in assessments resolved through discussion with the assistance of third reviewer. Based on the initial scoping of the available literature, most of the data will be from a broad range of studies, with a large range of potential biases. The following tools will be used: For randomised studies, we will use the Cochrane Risk of Bias 2 tool , conducting assessments at the outcome level when required69. The tool assesses the following domains bias arising from the randomisation process, bias to deviations from intended interventions, bias to missing outcome data, bias in measurement of the outcome, bias in selection of the reported result, with each domain receiving a judgement of low, some concerns and high risk of bias. An overall rating of bias will be determined by the worst risk of bias in any of the domains. However, if a study is judged to have “some concerns” about risk of bias for multiple domains, it might be judged as at high risk of bias overall. For non-randomised quantitative studies, we will use the Cochrane Risk of Bias in Non-randomised Studies - of Interventions tool (ROBINS-I)70. The tool assesses the following domains bias due to confounding, bias in selection of participants into the study, bias in classification of interventions, bias due to deviations from intended interventions, bias due to missing data, bias in measurement of outcomes, bias in selection of the reported result, with each domain receiving a judgement of low, moderate, serious, critical risk of bias. An overall rating of bias will be determined by if the study is comparable to a well performed randomised trial the study will be judged to be at low risk of bias for all domains. If the study provides sound evidence for a nonrandomised study but cannot be considered comparable to a well performed randomised trial, then it will be considered moderate risk of bias. However, if the study has some important problems, the study will be judged to be at serious risk of bias in at least one domain, but not at critical risk of bias in any domain. If the study has at least one domain at critical risk of bias then the study will be judged to be at critical risk of bias. Finally, if there is no clear indication that the study is at serious or critical risk of bias and there is a lack of information in one or more key domains of bias, the study will be considered as no information. We provide a detailed explanation of biases in each domain in Table A4. Qualitative studies, including mixed-methods studies reporting qualitative data, will be assessed using the Critical Appraisal Skill Programme, which is publicly available for use in educational and research settings71 and includes ten questions divided into three sections: validity, results, and relevance. The signalling questions have three possible answers: yes, no, can’t tell72 Where necessary, authors of the included studies will be contacted to request clarification or additional details related to their published results. This process aims to enhance data completeness for the review and does not involve the collection of new or original data from participants. Any disagreements that arise between the reviewers will be resolved through discussion, with the assistance of a third reviewer. The results of critical appraisal will be reported in narrative form and in a table. We will not exclude studies on the basis of their risk of bias but instead incorporate assessments into the synthesis process. According to the research objectives and due to the high heterogeneity expected in the studies, quantitative and qualitative data will be collected and analysed independently and then integrated during the synthesis stage. The extracted data will include specific details about population, PES components, contextual factors, and RoB assessment. To summarise key information from each study we will begin tabulating the data according to the objectives of the research as: impacts of PES programmes on self-reported health, maternal and child mortality and morbidity, mental health, all-cause of mortality and healthcare use according to the programme characteristics, participant characteristics, contextual factors, and the potential mechanisms of how PES programmes may affect health and subjective wellbeing. For the quantitative data we will display estimates within a forest plot, when possible, to harmonise effect measures across the studies. We will perform an effect direction plot and calculate P values for effect direction, followed by a Harvest plot to study differences in effect across population subgroups. If two or more studies report the same outcome and are sufficiently homogenous, we will perform meta-analyses. Given the likely variability among studies, we will use random-effects models for meta-analysis. When meta-analysis is not possible or appropriate, we will consider the Synthesis Without Meta-analysis (SWiM) framework instead44,73. To make the best use of the available data we will use appropriate methods, such as descriptive statistics as well as harvest plots/effect direction plots/vote counting. A funnel plot will be generated to assess publication bias if there are 10 or more studies included in a meta-analysis. Subgroup analyses will be conducted where there are sufficient data to investigate. We will stratify meta-analyses and conduct meta-regression by study design, RoB, characteristics of the PES programme, participant characteristics (gender, socioeconomic position, disabilities, ethnicity, level of education and age, forest management governance), and contextual characteristics (socioeconomic context, political context, previous ecosystem conditions, geographic location, land ownership, community governance structures) where data allow. For the qualitative data we will conduct a framework analysis paying attention to contradictory data and making comparisons in findings across key characteristics related to our logic model such as the intervention characteristics, population subgroups, contextual factors, among others74. The results from each synthesis method included in this review will then be compared and organised into a cohesive argument to generate an overall configured analysis. This section will present a narrative summary that reflects the configured analysis of both quantitative and qualitative evidence. It will also compare the findings addressing the following questions: What are the impacts of PES programmes on health and subjective wellbeing? Does the impact of PES programmes on health and subjective wellbeing outcomes differ according to PES characteristics, participant characteristics, contextual characteristics? What are the potential mechanisms through which PES programmes may affect health and subjective wellbeing?68.

of data synthesis will be mapped against our initial logic model, to refine the theory of change and to assess the credibility of the assumed causal pathways. We will use sub-group analysis to explore heterogeneity by different treatment sub-groups. We will undertake the moderator analysis by the following groups of variables described according to our logic model: Methodology: study design, risk of bias. Intervention characteristics. Context (socioeconomic context, political context, previous ecosystem conditions, geographic location, land ownership, community governance structures). Participant characteristics (gender, disabilities, socioeconomic position, age, level of education, ethnicity) Funnel plots will be generated if we find ten or more studies of the same outcome to detect potential reporting biases. When testing asymmetry in funnel plots (small study effects), we will investigate whether the relationship between a measure of study size and the estimated intervention effect is asymmetrical75. For the qualitative and SWiM analysis, tables will be used to describe the synthesis of methods, limitations and subgroups of the review44. We will consider conducting meta-regression when ten or more studies are included within a meta-analysis. Before deciding which studies to include in the final synthesis, a sensitivity analysis will be performed to assess how the reported effects vary based on different study characteristics. We will accomplish this by reporting separately the low/moderate risk ROBINS-I studies. For the randomised studies we will report separately low and unclear risk studies. We will consider conducting meta-regression when ten or more studies are included within a meta-analysis. In this review, the certainty (previously referred to as quality) of evidence will be evaluated using Grading of Recommendations Assessment, Development, and Evaluation (GRADE)76. We will present the information in a 'Summary of findings' (SoF) table to understand the characteristics of the populations and intervention included in the review and review the outcome data from the available studies in a structured way. Using GRADE, we will reflect the extent to which we have confidence, or our level of certainty, that the estimates of effect are correct. For GRADE the certainty of evidence will be described as high, moderate, low, and very-low confidence, and the domains assessed will be risk of bias, inconsistency, indirectness, imprecision, and publication of bias.

of the certainty assessment for each outcome will be presented alongside other key information for included outcomes in a SoF table, as specified in the Cochrane Handbook. The outcomes intended to be included in the SoF table are: Self-reported health outcomes. Mental health outcomes. Maternal and child health outcomes. External causes of morbidity and mortality e.g. violence, alcohol and drug harms. All-cause mortality. Healthcare use. It is acknowledged that these planned outcomes may change during analysis due to data availability. However, it will be noted if there are critical outcomes for which there is a lack of available evidence. There are many Payments for Ecosystem Services (PES) programmes being implemented worldwide with potentially beneficial effects on environmental degradation and poverty alleviation12,14,25. PES programmes, as with many other policies, often lack a health perspective in evaluations. Currently, two systematic reviews assessed childhood infectious diseases but no other elements of health or subjective wellbeing30,38. The current protocol has been developed to systematically explore the potential negative and positive impacts of PES programmes on individuals and communities in receipt of economic incentives, with a broader health and subjective wellbeing perspective that contemplates outcomes such as happiness, life satisfaction, quality of life, respiratory diseases, health-related behaviours, depression, anxiety, suicide, maternal and child mortality and morbidity, malnutrition, among others. We theorise PES programmes as complex interventions, with their impact on outcomes varying by context, participant characteristics, and PES components. Therefore, we will anticipate that the reports of primary studies will be heterogeneous. Accordingly, this review will collect, synthesise and analyse the results of quantitative and qualitative studies to provide a wide-ranging perspective of the impact on health and subjective wellbeing of PES programmes. We expect this evidence will help to understand the potential implications of market-based policies of this type and will contribute to highlighting the importance of health perspectives when environmental policies are designed and implemented. Furthermore, we hope that this improved understanding can help policymakers to refine PES programmes so that beneficial health impacts can be maximised, and potential adverse health impacts minimised. Ethical approval and consent were not required. Open Science Framework (OSF): The impacts of payment for ecosystem services programmes on health and wellbeing: a systematic review protocol. Working DOI: 10.17605/OSF.IO/JK48H77: This project contains the following extended data Data file 1: Table A1. The table summarize the Population Exposure Comparator Outcome Studies (PECOS) criteria that will be used for the inclusion criteria of the studies. Data file 2. Table A2. Example of Search Strategy: The table describe the terms and example of the search strategy on CABI & Global Health, EconLit, and Medline database and will be adapted to the rest of the databases. Data file 3. Table A3. Data items for extraction: The table describe the main data items that will be collected from the data extraction process. Data file 4. Table A4. Description of Bias domains in ROBINS-I: The table described the different biases in the domains of ROBINS-I that will be consider in the Risk of Bias Assessment. Data file 5. PRISMA-P checklist. Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). Extended data Open Science Framework (OSF): The impacts of payment for ecosystem services programmes on health and wellbeing: a systematic review protocol. Working DOI: 10.17605/OSF.IO/JK48H77 Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). This protocol is reported according to the Preferred Reported Reporting Items for Systematic Review and Meta-analysis for protocols checklist (PRISMA-P 2015) and follows Cochrane Handbook and Systematic Reviews in the Social Science: A Practical Guide guidance78–80. The review will be carried out and reported according to PRISMA guidance and Synthesis Without Meta-Analysis (SWiM) in Systematic Reviews guidance44,79,80. Out team want to acknowledge to the leaders of the Ecuadorian communities who supported us with their invaluable time and feedback of their experiences and perspectives with Payment for Ecosystem Services programmes implemented in Ecuador. 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Publisher Full Text Author details Author details 1 MRC/CSO Social and Public Health Science Unit, Clarice Pears Building 90 Byres Road, University of Glasgow, Glasgow, G12 8TB, Scotland, UK 2 Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, E C090112, Ecuador 3 School of Health and Wellbeing, Clarice Pears Building 90 Byres Road, University of Glasgow, Glasgow G12 8TB, UK 4 City St George's, University of London, London, England, SW17 0RE, UK 5 Research Department, Center for Data and Knowledge Integration for Health, Salvador, Bahia, 40045060, Brazil 6 School of Economics, Federal University of Bahia, Salvador, Bahia, 40045060, Brazil 2 Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, E C090112, Ecuador 3 School of Health and Wellbeing, Clarice Pears Building 90 Byres Road, University of Glasgow, Glasgow G12 8TB, UK 4 City St George's, University of London, London, England, SW17 0RE, UK 5 Research Department, Center for Data and Knowledge Integration for Health, Salvador, Bahia, 40045060, Brazil 6 School of Economics, Federal University of Bahia, Salvador, Bahia, 40045060, Brazil Micaela Calderon Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Mhairi Campbell Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Daniel Kopasker Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Mercy J. Borbor-Cordova Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Valerie Wells Roles: Methodology, Resources, Software, Writing – Review & Editing Roles: Methodology, Resources, Software, Writing – Review & Editing Claire Niedzwiedz Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Batul Rojeab Bravo Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing J. Firmino de Sousa Filho Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Philip Broadbent Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing Jonathan R Olsen Roles: Data Curation, Writing – Review & Editing Roles: Data Curation, Writing – Review & Editing S Vittal Katikireddi Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Software, Writing – Review & Editing Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Software, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This project is funded by the National Institute for Health and Care Research (NIHR) under its Grant Reference Number NIHR134801. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. MCalderon, BRB, FF, MJB are funded by NIHR (NIHR134801). MC is funded by Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). JRO is funded by Medical Research Council (MC_UU_00022/) and Chief Scientist Office (SPHSU19). SVK and DK are funded by Medical Research Council (MC_UU_00022/2), European Research Council (949582), and Scottish Government Chief Scientist Office (SPHSU17). PB is funded by Wellcome Funded PhD at School of Health and Wellbeing, University of Glasgow (304823-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright © 2025 Calderon M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. metrics VIEWS $counts.viewCount downloads Citations CITE how to cite this article Calderon M, Campbell M, Kopasker D et al. The impacts of Payment for Ecosystem Services programmes on health and wellbeing: a systematic review protocol [version 1; peer review: 1 approved]. NIHR Open Res 2025, 5:55 (https://doi.org/10.3310/nihropenres.13928.1) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. track receive updates on this article Track an article to receive email alerts on any updates to this article. Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 03 Jul 2025 Views 0 How to cite this report: Freitas H. Reviewer Report For: The impacts of Payment for Ecosystem Services programmes on health and wellbeing: a systematic review protocol [version 1; peer review: 1 approved]. NIHR Open Res 2025, 5:55 (https://doi.org/10.3310/nihropenres.15136.r36472) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/5-55/v1#referee-response-36472 https://openresearch.nihr.ac.uk/articles/5-55/v1#referee-response-36472 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Reviewer Report 19 Aug 2025 Approved VIEWS 0 Overall, this is a well-prepared, methodologically robust systematic review protocol with strong potential to inform both environmental and public health policy debates. Improvements would come from refining the scope, simplifying certain sections for clarity, and developing strategies to handle the ... Continue reading I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close Overall, this is a well-prepared, methodologically robust systematic review protocol with strong potential to inform both environmental and public health policy debates. Improvements would come from refining the scope, simplifying certain sections for clarity, and developing strategies to handle the anticipated diversity of study designs and outcomes. Highlight contribution: 1. A shift from environmental-only outcomes to a health and wellbeing focus. Most prior PES reviews concentrate on environmental effectiveness or livelihoods, often treating health outcomes as peripheral or as proxies (e.g., income, poverty rates). This review directly targets both objective and subjective health outcomes, from respiratory diseases to happiness and life satisfaction, enabling a broader and deeper assessment of human impacts. It moves beyond disease-specific evidence (such as malaria or diarrhoea in children) to systematically assess multiple health domains. Major Strengths This protocol demonstrates several notable strengths that position it as a potentially influential contribution to both environmental and public health research. First, its clear relevance and novelty stand out: the review addresses a significant gap in the literature by focusing on the health and subjective wellbeing impacts of PES programmes, a domain where existing reviews are scarce and fragmented. The protocol is built on a strong methodological framework, applying PECOS criteria, adhering to PRISMA-P guidelines, and aligning with Cochrane and SWiM guidance. This ensures methodological rigour throughout. Importantly, the integration of quantitative and qualitative evidence via a convergent segregate approach enables the review to capture not only statistical effect sizes but also the contextual, lived-experience insights crucial to understanding complex interventions like PES. A comprehensive search strategy further strengthens the protocol, combining multiple academic databases with grey literature sources such as WHO, FAO, and the World Bank, while including studies in English, Spanish, and Portuguese to broaden the evidence base and reduce language bias. The conceptual foundation is thoughtful and participatory, with a well-developed logic model that clearly articulates behavioural, material resource, and environmental mechanisms, informed by community leader feedback. The review also demonstrates a focus on equity and heterogeneity, with planned subgroup analyses on gender, socioeconomic position, governance structures, and contextual factors to enhance policy relevance. Finally, the policy-oriented dissemination plan, committing to share findings with policymakers and community leaders, ensures that the work has practical as well as academic utility. Areas for Improvement Despite its strengths, there are areas where the protocol could be refined. The length and complexity of the background section may faint the central research questions for non-specialist readers, suggesting a need for more concise framing. The scope is also potentially overly broad, covering a wide range of health and wellbeing outcomes without clear prioritisation, which could complicate synthesis and weaken conclusions. Engagement with Patient and Public Involvement is currently limited to the development of the logic model, and sustained involvement throughout interpretation and dissemination could improve legitimacy and contextual relevance. Including both randomised and varied non-randomised designs across diverse contexts introduces a risk of unmanageable heterogeneity, potentially limiting the feasibility of meta-analysis. The inclusion of grey literature, while valuable, also presents quality appraisal challenges that must be managed to avoid bias. In addition, while bias assessment tools such as ROBINS-I and CASP are specified, operational clarity is lacking on how conflicting assessments will be resolved during synthesis. Finally, while the logic model is well-articulated, some hypothesised pathways (e.g., violence risks from monitoring, long-term cancer outcomes) may have limited empirical support, creating a risk of overreaching conclusions. Highlight contribution: 1. A shift from environmental-only outcomes to a health and wellbeing focus. Most prior PES reviews concentrate on environmental effectiveness or livelihoods, often treating health outcomes as peripheral or as proxies (e.g., income, poverty rates). This review directly targets both objective and subjective health outcomes, from respiratory diseases to happiness and life satisfaction, enabling a broader and deeper assessment of human impacts. It moves beyond disease-specific evidence (such as malaria or diarrhoea in children) to systematically assess multiple health domains. Major Strengths This protocol demonstrates several notable strengths that position it as a potentially influential contribution to both environmental and public health research. First, its clear relevance and novelty stand out: the review addresses a significant gap in the literature by focusing on the health and subjective wellbeing impacts of PES programmes, a domain where existing reviews are scarce and fragmented. The protocol is built on a strong methodological framework, applying PECOS criteria, adhering to PRISMA-P guidelines, and aligning with Cochrane and SWiM guidance. This ensures methodological rigour throughout. Importantly, the integration of quantitative and qualitative evidence via a convergent segregate approach enables the review to capture not only statistical effect sizes but also the contextual, lived-experience insights crucial to understanding complex interventions like PES. A comprehensive search strategy further strengthens the protocol, combining multiple academic databases with grey literature sources such as WHO, FAO, and the World Bank, while including studies in English, Spanish, and Portuguese to broaden the evidence base and reduce language bias. The conceptual foundation is thoughtful and participatory, with a well-developed logic model that clearly articulates behavioural, material resource, and environmental mechanisms, informed by community leader feedback. The review also demonstrates a focus on equity and heterogeneity, with planned subgroup analyses on gender, socioeconomic position, governance structures, and contextual factors to enhance policy relevance. Finally, the policy-oriented dissemination plan, committing to share findings with policymakers and community leaders, ensures that the work has practical as well as academic utility. Areas for Improvement Despite its strengths, there are areas where the protocol could be refined. The length and complexity of the background section may faint the central research questions for non-specialist readers, suggesting a need for more concise framing. The scope is also potentially overly broad, covering a wide range of health and wellbeing outcomes without clear prioritisation, which could complicate synthesis and weaken conclusions. Engagement with Patient and Public Involvement is currently limited to the development of the logic model, and sustained involvement throughout interpretation and dissemination could improve legitimacy and contextual relevance. Including both randomised and varied non-randomised designs across diverse contexts introduces a risk of unmanageable heterogeneity, potentially limiting the feasibility of meta-analysis. The inclusion of grey literature, while valuable, also presents quality appraisal challenges that must be managed to avoid bias. In addition, while bias assessment tools such as ROBINS-I and CASP are specified, operational clarity is lacking on how conflicting assessments will be resolved during synthesis. Finally, while the logic model is well-articulated, some hypothesised pathways (e.g., violence risks from monitoring, long-term cancer outcomes) may have limited empirical support, creating a risk of overreaching conclusions. - Is the rationale for, and objectives of, the study clearly described? Yes - Is the study design appropriate for the research question? Yes - Are sufficient details of the methods provided to allow replication by others? Partly - Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Ecosystem Services CITE HOW TO CITE THIS REPORT Freitas H. Reviewer Report For: The impacts of Payment for Ecosystem Services programmes on health and wellbeing: a systematic review protocol [version 1; peer review: 1 approved]. NIHR Open Res 2025, 5:55 (https://doi.org/10.3310/nihropenres.15136.r36472) The direct URL for this report is: https://openresearch.nihr.ac.uk/articles/5-55/v1#referee-response-36472 https://openresearch.nihr.ac.uk/articles/5-55/v1#referee-response-36472 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. Alongside their report, reviewers assign a status to the article: - Approved - Approved with reservations - Not approved | Invited Reviewers | | |---|---| | 1 | | | Version 1 03 Jul 25 | read | Sign up for content alerts You are now signed up to receive this alert Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. 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