Agriculture, Forestry And Other Land Use Research Articles

Synthesising Mitigation Ambitions and Implementation of Agriculture, Forestry and Other Land Use (AFOLU) Sector

Synthesising Mitigation Ambitions and Implementation of Agriculture, Forestry and Other Land Use (AFOLU) Sector

Investigating the Nexus Between GHG Emissions and AFOLU Activities: New Insights from C-Vine Copula Approach

AbstractThe greenhouse gas (GHG) emissions from agriculture, forestry, and other land use (AFOLU) account for more than 10% of the total GHG emissions in Iran. To reduce the environmental impact, assessments of Iran’s GHG emissions status are critical for identifying the national policies to achieve Sustainable Development Goals (SDGs) in the bio-based industry. However, there is no study exploring the dependency between AFOLU and GHG emissions in Iran by using the Vine Copula approach. Hence, the study aims to examine the causality direction and correlation structure among selected horticulture, farming crops, livestock, and poultry products and carbon dioxide (CO2), nitrogen dioxide (N2O), and methane emissions (CH4) in the Iranian agriculture sector over the period 1961–2019, to determine which crops or products are more responsible to deteriorate the environment. The empirical strategy used a C-Vine Copula model to measure the correlations together with the Granger causality (GC) test to analyze the causality links. According to the empirical findings, several crops and products are the sources of emissions. Rice and vegetable cultivations, as well as meat and milk products (Kendall’s τ values of 0.37, 0.33, 0.31, and 0.31, respectively), are the leading sources of CH4 emissions. Legumes, eggs, maize, rice, and milk enhance N2O emissions, while CO2 emissions are caused by apple, potato, and apricot crops (Kendall’s τ values of 0.22, 0.18, and 0.16, respectively). Finally, based on the findings, policy implications are offered.

Development of Activity Data for Greenhouse Gas Inventory in Settlements in South Korea

In South Korea, Agriculture, Forestry, and Other Land Use (AFOLU) collates greenhouse gas (GHG) inventories. However, the settlement category lacks a clear definition of land use and activity data. This study proposed a method for examining the settlement spatial extent and constructing activity data to estimate GHG emissions and absorption as a pilot calculation, as well as to provide data for land use classification. Utilizing cadastral maps (CDMs), settlement spatial extents were determined, with settlements occupying approximately 11% of the total land area in 2019, or 9% excluding overlaps. Activity data for settlements were established through a sampling method and analysis of aerial orthoimages from 2000 and 2019. After removing overlaps with digital forest type maps and smart farm maps, settlement activity data covered approximately 18.47% based on CDMs, or 12.66% excluding overlaps. In 2019, CO2 emissions and absorptions were estimated at 622.16 ktCO2yr−1 based on CDMs and 242.16 ktCO2yr−1, excluding overlaps. To enhance GHG inventory calculation consistency and compliance with TACCC principles, clear spatial extents for settlements must be established. This entails constructing activity data and assessing GHG inventories accordingly. GHG inventory statistics should also inform future nationally determined contributions.

Application of the domain adaptation method using a phenological classification framework for the land-cover classification of North Korea

Efforts to achieve carbon neutrality are global, encompassing a wide range of factors. For the estimation of greenhouse gas emissions from the agriculture, forestry, and other land use (AFOLU) sector, the Intergovernmental Panel on Climate Change has proposed an advanced method that requires Approach 3, the highest level of suggested method, of activity data. Accordingly, we propose a phenological classification framework (PCF) that can perform land-cover classification by training the climatic repeatability of the annual cycle using a U-Net deep learning model. Additionally, the domain adaptation (DA) method can be applied to classify areas with insufficient data. We applied these methods to classify North Korea (i.e., using South Korean data), with an accuracy of 81.31%; overall this effort culminated in the simultaneous classification of the Korean Peninsula. Domain distribution comparison showed that the results for the two regions were similar. The PCF and DA methods proposed in this study allow for annual production of a land-cover map and change matrix, regardless of the presence or absence of data. The application of these methods is expected to provide a scientific basis for policy decisions that can facilitate the global attainment of carbon neutrality.

Unveiling The Nexus: Exploring the Impact of Behavioral Finance on Green Finance Initiatives

This research paper delves into the dynamic landscape of global climate finance during the fiscal years of 2021/2022, examining the collaborative efforts of public and private actors in addressing the multifaceted challenges posed by climate change. The equitable distribution of financial resources reflects a shared commitment to transformative action, with a focus on critical sectors such as energy, transport, and buildings and infrastructure. Both sectors emphasize the transition to renewable energy, sustainable transportation, and climate-resilient urban development. Public finance plays a pivotal role by directing support to relatively underserved sectors, including Agriculture, Forestry, and Other Land Use (AFOLU), water and wastewater management, and industry. This targeted intervention ensures inclusivity in climate action and contributes to broader sustainable development goals. The financial commitments not only reduce carbon footprints but also foster innovation, job creation, and economic resilience. The collaborative model of climate finance observed during this period sets a precedent for future endeavors, emphasizing a holistic and inclusive approach. The research suggests potential avenues for future studies, such as assessing the long-term impact of climate finance, evaluating evolving patterns in public-private collaboration, and exploring the integration of climate finance within global policy frameworks. Ultimately, this research contributes to the ongoing discourse on climate resilience, offering insights into the interconnectedness of financial commitments, sustainable development, and the global fight against climate change.

Pantropical CO2 emissions and removals for the AFOLU sector in the period 1990–2018

Transparent, accurate, comparable, and complete estimates of greenhouse gas emissions and removals are needed to support mitigation goals and performance assessments under the Paris Agreement. Here, we present a comparative analysis of the agriculture forestry and other land use (AFOLU) emission estimates from different datasets, including National Greenhouse Gas Inventories (NGHGIs), FAOSTAT, the BLUE, OSCAR, and Houghton (here after updated H&N2017) bookkeeping models; Emissions Database for Global Atmospheric Research (EDGAR); and the US Environmental Protection Agency (EPA). We disaggregate the fluxes for the forestry and other land use (FOLU) sector into forest land, deforestation, and other land uses (including non-forest land uses), while agricultural emissions are disaggregated according to the sources (i.e., livestock, croplands, rice cultivation, and agricultural fires). Considering different time periods (1990–1999, 2000–2010, and 2011–2018), we analyse the trend of the fluxes with a key focus on the tropical regions (i.e., Latin America, sub-Saharan Africa, and South and Southeast Asia). Three of the five data sources indicated a decline in the net emissions over the tropics over the period 1990–2018. The net FOLU emissions for the tropics varied with values of 5.47, 5.22, 4.28, 3.21, and 1.17 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs, respectively) over the recent period (2011–2018). Gross deforestation emissions over the same period were 5.87, 7.16, 5.48, 3.96, and 3.74 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs). The net forestland sink was −1.97, −3.08, −2.09, −0.53, and −3.00 GtCO2 year−1 (for BLUE, OSCAR, updated H&N2017, FAOSTAT, and NGHGIs). Continental analysis indicated that the differences between the data sources are much large in sub-Saharan Africa and South and Southeast Asia than in Latin America. Disagreements in the FOLU emission estimates are mainly explained by differences in the managed land areas and the processes considered (i.e., direct vs indirect effects of land use change, and gross vs net accounting for deforestation). Net agricultural emissions from cropland, livestock, and rice cultivation were more homogenous across the FAOSTAT, EDGAR, and EPA datasets, with all the data sources indicating an increase in the emissions over the tropics. However, there were notable differences in the emission from agricultural fires. This study highlights the importance of investing and improving data sources for key fluxes to achieve a more robust and transparent global stocktake.

Stakeholder-based modelling in climate change planning for the agriculture sector in Argentina

ABSTRACT The development of long-term scenarios to outline pathways for achieving carbon neutrality by 2050 has become a standard practice in climate change policy planning. In Argentina, a modelling process was initiated in 2019 in the agriculture, forestry and other land use (AFOLU) sector utilizing three tools: FABLE calculator, Dinamica EGO and Nature Map. In order to generate technical inputs for the modelling exercise a stakeholder dialogue was launched. A 2050 Carbon Neutrality scenario was developed, alongside several intermediate scenarios based on stakeholders´ visions of the future. The modelling results demonstrated the biophysical feasibility of achieving carbon neutrality in the Argentinean AFOLU sector by 2050. However, alignment with current sectoral priorities was identified as a challenge, leading stakeholders to propose less ambitious scenarios as more attainable targets. This experience underscored the significance of constructing multiple policy scenarios, facilitating the evaluation of diverse potential future trajectories for policymaking. These different pathways provided contrasting perspectives between political objectives, such as achieving carbon neutrality, and the practical feasibility of local implementation. Moreover, the process highlighted the vital role of integrating the private sector and environmental non-governmental organizations (NGOs) in long-term climate planning, emphasizing the need for inclusive collaboration to address climate challenges effectively.

Linking climate policy across economic sectors: A case for green growth in Nepal

AbstractWhile the energy sector is the largest global contributor to greenhouse gas (GHG) emissions, the agriculture, forestry, and other land use (AFOLU) sector account for up to 80% of GHG emissions in the least developed countries (LDCs). Despite this, the nationally determined contributions (NDCs) of LDCs, including Nepal, focus primarily on climate mitigation in the energy sector. This paper introduces green growth—a way to foster economic growth while ensuring access to resources and environmental services—as an approach to improving climate policy coherence across sectors. Using Nepal as a case country, this study models the anticipated changes in resource use and GHG emissions between 2015 and 2030, that would result from implementing climate mitigation actions in Nepal's NDC. The model uses four different scenarios. They link NDC and policies across economic sectors and offer policy insights regarding (1) energy losses that could cost up to 10% of gross domestic product (GDP) by 2030, (2) protection of forest resources by reducing the use of biomass fuels from 465 million gigajoules (GJ) in 2015 to 195 million GJ in 2030, and (3) a significant reduction in GHG emissions by 2030 relative to the business‐as‐usual (BAU) case by greater use of electricity from hydropower rather than biomass. These policy insights are significant for Nepal and other LDCs as they seek an energy transition towards using more renewable energy and electricity.

Quantifying greenhouse gas emissions from wood fuel use by households

Abstract. The combustion of wood fuel for residential use is often not considered to be a source of greenhouse gas (GHG) emissions from households, as the emissions from wood fuel combustion can be offset by the CO2 absorbed by the growth of the forest (as a carbon sink) (IPCC, 2006). However, this only applies to wood that is harvested in a renewable way, i.e. at a rate not exceeding the regrowth rate of the forest from which it was harvested (Drigo et al., 2002). This paper estimates the share of GHG emissions attributable to non-renewable wood fuel harvesting for use in residential food activities, by country and with global coverage. It adds to a growing research base estimating GHG emissions from across the entire agri-food value chain, from the manufacture of farm inputs, through food supply chains, and finally to waste disposal (Tubiello et al., 2021). Country-level information is generated from United Nations Statistics Division (UNSD) and International Energy Agency (IEA) data on wood fuel use by households. We find that, in 2019, annual emissions from non-renewable wood fuel consumed for household food preparation were about 745×106 t (Mt CO2 eq. yr−1), with an uncertainty ranging from −63 % to +64 %. Overall, global trends were a result of counterbalancing effects: the emission increases were largely fuelled by countries in sub-Saharan Africa, southern Asia, and Latin America, whereas significant decreases were seen in countries in eastern Asia and South-East Asia. The Food and Agriculture Organization of the United Nations (FAO) has developed and regularly maintains a database covering GHG emissions from the various components of the agri-food sector, including pre- and post-production activities, by country and world regions. The dataset has been developed according to the International Panel on Climate Change guidelines (IPCC, 2006), which avoid overlaps between agriculture, forestry, and other land use (AFOLU) and energy components. The aforementioned dataset relies mainly on UNSD Energy Statistics data, which are used as activity data for the calculation of the GHG emissions (Tubiello et al., 2022). The information used in this work is available as open data at https://doi.org/10.5281/zenodo.7310932 (Flammini et al., 2022a).

A SHOCK RESPONSE MODEL IN GROWING GREENHOUSE GAS EMISSIONS

The present article identified what would be the impacts on the productive quantity of five large agricultural segments, if there was an increase in GHG emissions in Brazil. Methodologically, a Structural Vector Auto Regression Model was structured and operated with data between the years 1970 and 2018. The following information was used: the level of emissions produced by the Agriculture, Forestry and Other Land Use (AFOLU) sector, the quantity of sugarcane, corn and coffee produced, as well as the cattle and swine breeding stock. In general, the results obtained reveal the importance of controlling the level of emissions generated, as there was a reduction in the production of all studied segments. Thus, considering emissions from AFOLU, it is concluded that all sectors chosen for the study will suffer losses in production if there is no control over future emissions, indicating the need for pro-environmental public policies for the agricultural sectors.

Toward a roadmap for space-based observations of the land sector for the UNFCCC global stocktake.

Space-based remote sensing can make an important contribution toward monitoring greenhouse gas emissions and removals from the agriculture, forestry, and other land use (AFOLU) sector, and to understanding and addressing human-caused climate change through the UNFCCC Paris Agreement. Space agencies have begun to coordinate their efforts to identify needs, collect and harmonize available data and efforts, and plan and maintain a long-term roadmap for observations. International cooperation is crucial in developing and realizing the roadmap, and the Committee on Earth Observation Satellites (CEOS) is a key coordinating driver of this effort. Here, we first identify the data and information that will be useful to support the global stocktake (GST) of the Paris Agreement. Then, the paper explains how existing and planned space-based capabilities and products can be used and combined, particularly in the land use sector, and provides a workflow for their harmonization and contribution to greenhouse gas inventories and assessments at the national and global level.

Food Production and Amazon Preservation are Not Mutually Exclusive: Exploring Feasible Avenues from the Perspective of Land Use Related NDCs in Brazil

The COP21 Paris Agreement and Nationally Determined Contributions (NDC) have proven to be milestones in the operationalization of climate action at the country-level, particularly in the Agriculture, Forestry and Other Land Use (AFOLU) sector. In Brazil, AFOLU-related NDC actions in its first version envisaged the elimination of, for instance: illegal deforestation in the Amazon region, the restoration and reforestation of 12 million hectares of severely degraded lands, and the substantial expansion of sustainably produced biofuels by 2030. While Brazilian Government commitment to these NDC targets soon vanished, a specific analytical question concerns as to how far sustainable land use scenarios can contribute to non-climate benefits (i.e., socioeconomic development) despite their internal challenges of harmonizing them with environmental protection and climate change mitigation. In this paper, we analyse the potential socioeconomic and environmental synergies and trade-offs in NDC implementation, given the possibility of the demand for land in Brazil increase due to agricultural and livestock expansion. We focus our analysis on GDP growth, income distribution, and food security. We do so by integrating land-use with computable general equilibrium (CGE) models and running policy scenarios, emulating different levels of NDC and development policy implementation. Our analysis helps us to understand how social and economic outcomes do change under varying levels of commitment by decision-makers. It shows that NDC implementation in Brazil is preferable to a business-as-usual development pathway, particularly when climate change is taken into consideration. While GDP and household income appear unaffected by NDC implementation, reducing the pressure over Amazon deforestation along with other social benefits appears under more stringent NDC implementation. Those results are particularly important given the significant upward trend in Amazon deforestation recorded in the last few years and the loss of purchasing power of low-income classes observed since 2015 in Brazil. In the AFOLU sector, NDC implementation, as in its first version, could thus act as entry points for alternative development pathways. For instance, such as the ones discussed under green economy or low carbon growth paradigms - although, possible trade-offs between agricultural and other sectors will still need to be closely monitored.

Land use and environmental quality in Ireland over two decades of contrasting agricultural trends

Global awareness and scrutiny of food production systems, including competition for land between agriculture and nature-based solutions to climate change, has increased immensely recently. In Ireland, around 70% of land area is used for agriculture, mostly pasture-based livestock production. Cattle numbers began to decline in the late 1990s, as milk productivity per cow increased along with the European Union policy of intensification implemented in 1998. Phasing out of the EU milk quota system from 2011 onwards initiated an increase in dairy cow numbers, which rose by 46% by 2020. This development has reversed environmental progress. This study outlines the impact of contrasting policies that have contributed to abatement and intensification of greenhouse gas and ammonia emissions from Ireland’s agriculture, forestry and other land use (AFOLU) sector, along with impacts on water quality effects. Ireland achieved most environmental targets during the 2000s. However, between 2010 and 2019, agricultural greenhouse gas emissions increased by 12% and annual ammonia emission ceilings exceeded the national limit in seven of those years. Around 6% of rivers lost their good or high ecological water quality status. These developments jeopardise compliance with contemporary environmental targets, such as achieving a 25% reduction in greenhouse gas emissions from agriculture by 2030, and AFOLU climate neutrality by 2050. Achieving environmental quality targets will necessitate far-reaching and immediate development of policy for the land use sector beyond the implementation of currently proposed mitigation measures.

Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement

Transformation pathways for the land sector in line with the Paris Agreement depend on the assumption of globally implemented greenhouse gas (GHG) emission pricing, and in some cases also on inclusive socio-economic development and sustainable land-use practices. In such pathways, the majority of GHG emission reductions in the land system is expected to come from low- and middle-income countries, which currently account for a large share of emissions from agriculture, forestry and other land use (AFOLU). However, in low- and middle-income countries the economic, financial and institutional barriers for such transformative changes are high. Here, we show that if sustainable development in the land sector remained highly unequal and limited to high-income countries only, global AFOLU emissions would remain substantial throughout the 21st century. Our model-based projections highlight that overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. While also a scenario purely based on either global GHG emission pricing or on inclusive socio-economic development would achieve the stringent emissions reductions required, only the latter ensures major co-benefits for other Sustainable Development Goals, especially in low- and middle-income regions.

Blue carbon sinks in South Africa and the need for restoration to enhance carbon sequestration

Blue carbon ecosystems (mangroves, salt marshes, and seagrasses) contribute towards climate change mitigation because they are efficient at sequestering atmospheric CO2 into long-term total ecosystem carbon stocks. Destruction or disturbance therefore reduces sink capacity and leads to significant CO2 emissions. This study reports the first national estimates of: 1) total carbon storage, 2) CO2 emissions from anthropogenic activities, 3) the potential for restoration to enhance carbon sequestration for blue carbon ecosystems in South Africa. Mangrove ecosystems have the greatest carbon storage per unit area (253–534 Mg C ha−1), followed by salt marshes (100–199 Mg C ha−1) and seagrasses (45–144 Mg C ha−1). Salt marshes are the most extensive and contribute 67 % to the national carbon stock of 4000 Gg C. Since 1930, 6500 ha has been lost across all blue carbon ecosystems (26 % of the natural extent), equivalent to losing 1086 Gg C from the national carbon stock. Historic CO2 emissions were estimated at an average rate of 30,266 t CO2e yr−1. Despite losses, a total of 3998 ha could be restored to increase carbon sequestration and CO2 removals of 14,845 tCO2e.yr−1. Extractive activities have declined rapidly in recent decades, but abiotic pressures on estuarine ecosystems (flow modification, reduced water quality, and artificial breaching) have been increasing. There is an urgent need to quantify the potential impact of these pressures and include them in estuarine management and restoration plans. Blue carbon ecosystems cover a relatively small area in South Africa, but they are valued for their multiple ecosystem services that contribute towards climate change adaptation and biodiversity co-benefits. These ecosystems need to be included in national policies driving climate change response in the Agriculture, Forestry and Other Land-Use (AFOLU) sector, such as incorporating them into the wetland subcategory of the national GHG inventory.

CARBON EMISSION INTENSITY FOR MELAKA GREEN TECHNOLOGY CITY STATE

The study analyzes the carbon emission absolute number and intensity for Melaka state as a response to the Malaysia voluntary reduction target of up to 40 percent in terms of emissions intensity of gross domestic product, GDP by the year 2030 compared to 2005 levels. It is manifested in the vision of Melaka Green Technology city state by 2020. The Global Protocol for Community-Scale Greenhouse Gas Emissions, GPC method deploys to calculate greenhouse gas, GHGs emission resulted from the various development activity in Melaka. This method classified GHG emissions into four (4) mains sectors: stationary energy, transportation, waste, and agriculture, forestry, and other land use (AFOLU) by using secondary data from related government agencies at the state level. The computation by BASIC+ reporting level resulted from an output of GHGs emission translated into carbon emission. Steady increase of GHG emissions was captured from 8,859,802 tCO2e (2013) to 8,911,173 tCO2e (2017). Further, carbon emission intensity calculates by gathering the carbon emission absolute number to Melaka’s population. The emission per-capita increase from 6.19 tCO2e (2013) to 6.88 tCO2e (2017), indicates each person contributes to the increment of GHGs emissions for Melaka state. However, the decrease of emission intensity records from 0.189 tCO2e (2013) to 0.176 tCO2e (2017) compared to an increase in population growth. The study concludes certain influences of the aggressive green technology initiative effect, such as renewable energy, LED street lighting, solar valley, smart metering in the building, electric public bus, no plastic bag, waste recycling to the overall carbon emission intensity of Melaka Green technology City State.

The role of food and land use systems in achieving India’s sustainability targets

The food and land use sector is a major contributor to India’s total greenhouse gas (GHG) emissions. On one hand, India is committed to sustainability targets in the Agriculture, Forestry and Other Land Use (AFOLU) sectors, on the other, there is little clarity whether these objectives can align with national developmental priorities of food security and environmental protection. This study fills the gap by reviewing multiple corridors to sustain the AFOLU systems through an integrated assessment framework using partial equilibrium modeling. We create three pathways that combine the shared socio-economic pathways with alternative assumptions on diets and mitigation strategies. We analyze our results of the pathways on key indicators of land-use change, GHG emissions, food security, water withdrawals in agriculture, agricultural trade and production diversity. Our findings indicate that dietary shift, improved efficiency in livestock production systems, lower fertilizer use, and higher yield through sustainable intensification can reduce GHG emissions from the AFOLU sectors up to 80% by 2050. Dietary shifts could help meet EAT-Lancet recommended minimum calorie requirements alongside meeting mitigation ambitions. Further, water withdrawals in agriculture would reduce by half by 2050 in the presence of environmental flow protection and mitigation strategies. We conclude by pointing towards specific strategic policy design changes that would be essential to embark on such a sustainable pathway.

GOBLIN version 1.0: a land balance model to identify national agriculture and land use pathways to climate neutrality via backcasting

Abstract. The Paris Agreement commits 197 countries to achieve climate stabilisation at a global average surface temperature less than 2 ∘C above pre-industrial times using nationally determined contributions (NDCs) to demonstrate progress. Numerous industrialised economies have targets to achieve territorial climate neutrality by 2050, primarily in the form of “net zero” greenhouse gas (GHG) emissions. However, particular uncertainty remains over the role of countries' agriculture, forestry, and other land use (AFOLU) sectors for reasons including the potential trade-offs between GHG mitigation and food security, a non-zero emission target for methane as a short-lived GHG, and the requirement for AFOLU to act as a net sink to offset residual emissions from other sectors. These issues are represented at a coarse level in integrated assessment models (IAMs) that indicate the role of AFOLU in global pathways towards climate stabilisation. However, there is an urgent need to determine appropriate AFOLU management strategies at a national level within NDCs. Here, we present a new model designed to evaluate detailed AFOLU scenarios at national scale using the example of Ireland, where approximately 40 % of national GHG emissions originate from AFOLU. GOBLIN (General Overview for a Backcasting approach of Livestock INtensification) is designed to run randomised scenarios of agricultural activities and land use combinations within biophysical constraints (e.g. available land area, livestock productivities, fertiliser-driven grass yields, and forest growth rates). Using AFOLU emission factors from national GHG inventory reporting, GOBLIN calculates annual GHG emissions out to the selected target year for each scenario (2050 in this case). The long-term dynamics of forestry are represented up to 2120 so that scenarios can also be evaluated against the Paris Agreement commitment to achieve a balance between emissions and removals over the second half of the 21st century. Filtering randomised scenarios according to compliance with specific biophysical definitions (GHG time series) of climate neutrality will provide scientific boundaries for appropriate long-term actions within NDCs. We outline the rationale and methodology behind the development of GOBLIN, with an emphasis on biophysical linkages across food production, GHG emissions, and carbon sinks at a national level. We then demonstrate how GOBLIN can be applied to evaluate different scenarios in relation to a few possible simple definitions of “climate neutrality”, discussing opportunities and limitations.

Community‐led peatland restoration in Southeast Asia: 5Rs approach

Peatlands in Southeast Asia are of global significance for biodiversity conservation and climate regulation as well as of national and local significance for water management and livelihood support. Despite this, these ecosystems are among the least studied and monitored of the world, and are increasingly threatened by anthropogenic activities. Peatland degradation is responsible for the largest greenhouse gases (GHGs) emission source from the agriculture, forestry, and other land use (AFOLU) sectors in the region. Peatland restoration is a key mitigation and preventative intervention to halt the degradation of these ecosystems. In recent years, a small number of studies have aimed to define peatland restoration processes and approaches, the latest being the 4Rs approach—Rewetting, Reduction of fire, Revegetation, and Revitalization. The latter component being focused on the local communities benefits, in terms of promoting diversified sustainable livelihoods. Based on evidence of successful peatland restoration interventions in Southeast Asia, which we define as being “community‐led,” we propose a 5Rs approach to peatland restoration instead, with community participation embedded in each component of the approach, beyond Revitalization, as well as in a fifth crosscutting component: Reporting and monitoring (R5). The new community‐led 5Rs approach can support the ongoing formulation, refinement and implementation of peatland restoration strategies and activities in Southeast Asia and beyond by achieving ecological restoration goals, while obtaining local communities endorsement and support, needed for the long‐term sustainability of the restoration interventions.

Forest cover changes and public policy: A literature review for post-conflict Colombia

Tackling deforestation remains a significant challenge in tropical countries and even more so in those affected by armed conflicts. This is partly because of the limited local understanding of the causes of forest cover changes (FCC) and how these causes relate to development. In this study, we use Colombia as a model to contribute to the understanding of the links between the causes of FCC in conflict-affected countries and policies aimed at achieving sustainable development by targeting the agriculture, forestry and other land use (AFOLU) sectors. Specifically, we reviewed studies reporting on causes of FCC from 1995 to 2019 to build a state-of-the-art review. We then identified relevant public policies targeting AFOLU sectors and used them as a proxy for development. Finally, we discussed the links between these public policies and FCC. From the reviewed literature, it is clear that research on FCC in Colombia has focused on understanding the causes of forest cover losses while disregarding forest cover gains. Although cattle ranching and agriculture dominate the literature as proximate causes of deforestation and policy and institutional factors as underlying causes of deforestation, the relative importance of proximate and underlying causes of FCC in Colombia has changed over time. The main categories of policies that have been linked to FCC deal with conflict and post-conflict issues, coca eradication and, more recently, the implementation of the peace agreement. Another set of policies frequently mentioned are those related to productive activities. In Colombia, these policies' effects on forests will depend on how the state will regulate extractive activities in a post-conflict scenario. Therefore, it is imperative to review and update policies to tackle FCC, mainly deforestation, to successfully achieve sustainability targets in Colombia.