The team’s fieldwork covered 16 plots across four land-use systems, each plot a 500-square-meter sampling unit designed to capture the internal variability of these ecosystems. In the coffee systems, located between 1,060 and 1,080 meters above sea level, the researchers measured every tree within their plots, recording trunk diameter at breast height, total height, and wood density. These measurements fed into generalized allometric regression equations that estimate aboveground biomass from trunk dimensions and wood basal density, with species-level wood density values drawn from the Global Wood Density Database. Where species data were unavailable, the team used genus or family averages. Belowground biomass was estimated using root-to-shoot ratios developed for tropical highland forests, and a standard carbon fraction of 50 percent was applied to convert dry biomass into carbon, a figure consistent with IPCC default values of 0.47 to 0.50 for tropical woods.

The results are unambiguous. Primary forests stored approximately 133.74 tonnes of aboveground carbon per hectare and 40.12 tonnes of belowground carbon per hectare, equivalent to roughly 638.05 tonnes of carbon dioxide per hectare when the carbon is converted to its CO2 equivalent. The coffee systems, by comparison, stored dramatically less. Among them, the agroforestry coffee system with mixed shade trees performed best, followed by coffee grown with Inga, while the monoculture system consistently registered the lowest values across every carbon metric. The statistical models, fitted with Gamma distributions and generalized linear mixed models in R, achieved adjusted R-squared values exceeding 99 percent, confirming that the differences in carbon storage were overwhelmingly associated with the type of ecosystem rather than random variation.

Biodiversity followed the same gradient. Using the Shannon index, Simpson index, and Pielou evenness index, the researchers found that primary forests hosted the highest species richness and the most balanced distribution of individuals across all metrics, with statistically significant differences at p < 0.01. The agroforestry coffee system maintained a species richness of 6.25, though its lower evenness value of 0.42 suggested that a few dominant species shaped the community. Coffee grown with Inga showed lower richness at 2.0 but moderate evenness at 0.58, while the monoculture system presented minimal diversity, reflecting a simplified community dominated by very few species. The primary forest’s superior diversity may be linked to its higher elevation of 1,625 meters, where cooler temperatures and greater humidity favor the coexistence of more plant species.

When the researchers translated carbon storage into economic terms using Peru’s social cost of carbon of 7.1 US dollars per tonne, the primary forest’s value reached approximately 949.52 dollars per hectare in aboveground carbon alone, with additional valuations of 284.86 dollars per hectare in belowground carbon and 4,530.15 dollars per hectare when total CO2 storage was considered. The coffee systems, by contrast, registered values far below these figures, with the agroforestry system performing best among them and the monoculture worst. The economic gap between primary forest and any coffee system is so wide that the researchers describe forest conversion as generating significant losses in carbon-related benefits, losses that compound with every additional hectare cleared.

A sensitivity analysis tested how these valuations would shift under alternative carbon pricing scenarios. At low prices of 5 and 20 dollars per tonne of CO2, the economic differences between coffee systems narrowed considerably. But from 50 dollars per tonne upward, the gap widened, with the agroforestry coffee system standing out as the highest-value option among the coffee treatments, followed by coffee with Inga and then the monoculture. At 100 dollars per tonne, the greater structural complexity of the agroforestry system translated into a clearly visible relative economic advantage, suggesting that carbon markets could increasingly reward farmers who maintain shade trees and diverse canopy structures within their coffee plantations.

A principal component analysis integrating the ecological and economic data revealed that the first two axes explained 94.07 percent of total variation, with the first component capturing a robust gradient from simplified monoculture systems to complex, carbon-rich primary forests. The biplot positioned primary forests at the high end of total CO2, evenness, Shannon diversity, and Simpson index values, while the agroforestry coffee system clustered near species richness, and the monoculture sat at the opposite end of the gradient. Coffee with Inga occupied an intermediate position, suggesting a transitional state between low and high ecological complexity. This multivariate structure reinforces the biodiversity-functioning theory: ecosystems with greater species diversity tend to store more carbon because diverse communities use resources more complementarily, build more complex forest structures, and are more resilient to environmental disturbances.

The findings carry direct implications for climate policy in Peru and beyond. The researchers note that forests are expected to contribute roughly 10 percent of the mitigation required to limit global warming to 1.5 degrees Celsius, which would require carbon prices to reach approximately 281 dollars per tonne of CO2 by 2055. By comparison, the average carbon sequestration cost in northwest China has been estimated at 4.77 dollars per tonne, well below the 7.1 dollars per tonne applied in this study. Protecting forests in the Peruvian Amazon may require investments ranging from 7.97 to 10.45 dollars per tonne of CO2, figures that support the implementation of conservation strategies and increase the economic value of standing forests. The study’s authors argue that these valuations provide a technical basis for incorporating coffee agroforestry systems into Payments for Ecosystem Services schemes and for aligning coffee production models with Peru’s Nationally Determined Contributions under international climate agreements.

The research also speaks to the principles of REDD+ initiatives, which aim to conserve forests and increase carbon stocks through economic incentives. The observed transition from monoculture coffee to agroforestry systems represents a trajectory compatible with REDD+ objectives by simultaneously increasing stored carbon and biological diversity. The economic potential associated with conserving tree cover, rising from 174.06 dollars per hectare in monoculture to 4,530.15 dollars per hectare in primary forest, illustrates how market mechanisms such as PES and REDD+ can generate effective incentives when supported by strong institutions, transparent monitoring systems, and equitable distribution of benefits among local actors. In Latin America, which constitutes one of the main global suppliers of forest carbon credits, agroforestry systems hold particular promise for generating credits due to their CO2 capture capacity, though certification continues to face challenges related to additionality, permanence, and transparency of projects.

The authors acknowledge that their observational comparison carries limitations. The primary forest site sat more than 500 meters higher than the coffee systems, an altitudinal difference that could influence carbon dynamics, though previous research has shown that the loss of aboveground biomass from forest conversion dominates the carbon balance at all elevational levels. The models achieved high statistical fit, but uncertainty remains associated with ecosystem variability, biomass measurement, and the selection of allometric equations, meaning small changes in carbon estimates could modify the economic valuation of the ecosystem service. Nevertheless, the study’s central message is clear: conserving native forests remains the most effective strategy for maintaining carbon storage, biodiversity, and ecosystem services in the Peruvian Amazon, while promoting sustainable agroforestry practices offers a complementary pathway that rewards farmers for keeping trees on the land. As Peru grapples with continued forest loss, these findings provide the quantitative evidence needed to make standing forests economically competitive with the coffee that threatens to replace them.

Subject of Research: Carbon sequestration economics of forest-to-coffee conversion in the Peruvian Amazon

Article Title: Converting forests to coffee cultivation (Coffea arabica) significantly reduces organic carbon sequestration payments in the Peruvian Amazon

Article References: Gaona-Jimenez, N., Padilla-Macedo, B. T., Saucedo Vega, W., Ludena-Cárdenas, J. C., Zevallos Ruiz, M., Ríos Vargas, C., Martínez Quiroz, E. N., Gutiérrez López, J. F., Saavedra-Ramírez, J., Tuesta-Hidalgo, J. C., Tuesta-Hidalgo, O. A., Hidalgo Tuesta, J. J., Rengifo Amasifen, R. R., Juárez Rivero, A. A., Aldava Pardave, U., & Ordonez-Ruiz, K. M. (2026). Converting forests to coffee cultivation (Coffea arabica) significantly reduces organic carbon sequestration payments in the Peruvian Amazon. Frontiers in Environmental Economics, 5, Article 1905945. https://doi.org/10.3389/frevc.2026.1905945

Image Credits: AI Generated

DOI: 10.3389/frevc.2026.1905945

Keywords: carbon sequestration, Peruvian Amazon, coffee agroforestry, REDD+, payments for ecosystem services, biodiversity, Converting, forests, coffee, cultivation, Coffea, arabica

Green grabbing describes the appropriation of land and resources legitimized by environmental agendas, whether for biodiversity conservation, carbon sequestration, ecosystem services, ecotourism, or renewable energy production. The term emerged from the older concept of land grabbing, which gained prominence in 2008 after the global food price crisis triggered a wave of large-scale land acquisitions in the Global South by foreign investors seeking to secure agricultural production. But as the new analysis makes clear, environmental concerns themselves have become core drivers of land appropriation, creating novel forms of valuation and accumulation. Unlike classical land grabs, which rely on overt coercion or market mechanisms alone, green grabbing operates through a distinctive mechanism in which environmental justifications disarm opposition and attract support from constituencies unlikely to endorse conventional dispossession.

At the center of the debate is the conservation concession model, a contractual arrangement in which a government or landholder transfers management rights over a specified territory to a concessionaire, typically a conservation organization, private company, or hybrid entity, in exchange for payments or investments to achieve defined conservation outcomes. Proponents, including major international financial institutions and conservation organizations, frame these concessions as pragmatic and efficient mechanisms for protecting ecologically valuable landscapes while generating economic benefits for host nations. Crucially, contemporary concessions are increasingly funded not by philanthropic donations but by anticipated revenues from carbon credit sales, transforming the incentive structure from an ongoing donor subsidy to financial self-sufficiency through the commodification of forest carbon. This shift, the authors argue, fundamentally alters the politics of conservation.

To evaluate when a conservation intervention crosses the line into green grabbing, the researchers propose a set of analytical criteria drawn from critical agrarian studies and political economy. These include changes in access rights, dispossession or exclusion of land users, the absence of meaningful consent under the Free, Prior, and Informed Consent framework, inequitable distribution of costs and benefits, and the transfer of decision-making authority from customary institutions to external actors. The framework also examines how livelihoods are affected across natural, social, human, physical, and financial capital, and how power asymmetries shape who benefits and who loses from conservation interventions.

The empirical heart of the study lies in Malawi, where the authors draw on fifteen years of fieldwork experience, 67 key informant interviews, 12 focus group discussions, and non-participant observation conducted between December 2025 and March 2026. The primary case is the Mamaland carbon concession, announced in early 2026 as the most significant and controversial conservation initiative in the country’s history. The agreement involves the Portuguese construction conglomerate Mota-Engil, through its agroforestry subsidiary, and the Singaporean commodity trader Trafigura, who together will market carbon credits generated from 550,000 hectares of Malawian forest reserves over a 40-year period. The reserves include South Viphya, Dwambazi, Dzalanyama, Michiru, and Chimaliro, forests that surrounding communities have relied upon for generations.

The Mamaland concession exhibits what the authors identify as four critical governance failures. First, Malawi’s Forestry Act and Land Act contain no reference to carbon rights, meaning the ownership of carbon sequestered on forest reserves remains legally untested and potentially subject to dispute. Under the prevailing operational assumption that land or tree ownership confers carbon ownership, the concession effectively claims rights to ecosystem services that were never explicitly allocated through any legislative process. Second, no publicly disclosed benefit-sharing terms exist; the government’s framework suggests a 5 percent community entitlement, but its application remains unclear. Third, community leaders reported meetings that could not adequately explain how long the land would remain under concession or what share of revenue would return to local people, raising serious questions about whether genuine consent was ever obtained. Fourth, the 40-year term contains no review clause for renegotiation as carbon prices evolve, locking in communities and government to a fixed arrangement that exceeds standard cycles of democratic accountability.

The consequences of these design failures are not abstract. With over 96 percent of Malawian households relying on biomass for cooking fuel, restrictions on forest access for carbon preservation impose immediate costs on the most vulnerable populations. In practice, the avoided-deforestation model criminalizes traditional livelihood practices such as shifting cultivation, fuelwood collection, and the harvesting of non-timber forest products like medicinal plants, honey, and thatch grass. These activities constitute the daily subsistence strategies of surrounding communities, and their reclassification as illegal extraction risks exacerbating poverty and generating local resistance that ultimately undermines long-term conservation goals. As one key informant observed during a community meeting, if people are fenced out to protect the carbon, the result is not a project but a conflict.

The study also documents how conservation concessions reconfigure rural class dynamics. In Majete Wildlife Reserve, managed by African Parks under a delegated management agreement, new community-based organizations were established that report to park managers rather than to democratically elected village development committees, creating what community members describe as a parallel governance system. Employment opportunities are concentrated among those with formal education or political connections, while poorer households who rely more directly on common-pool resources for subsistence are disproportionately harmed by access restrictions. This pattern of differentiated dispossession empowers a new cadre of conservation-oriented elites while marginalizing the agrarian poor, a dynamic also documented in Madagascar, where the collapse of state capacity led to a stark division between high-paid foreign workers and low-wage local staff.

Yet the analysis is not uniformly pessimistic. The Kulera REDD+ Programme, operating in the Nyika and Vwaza landscapes of Malawi, demonstrates that inclusive benefit-sharing is operationally feasible when communities are structured as partners rather than passive beneficiaries. The Nyika-Vwaza Association and the Nkhotakota Wildlife Reserve Association employ their own staff, participate in carbon credit pricing decisions, and engage in participatory budgeting, with 25 percent of park resources and fees flowing to registered community associations. This stands in sharp contrast to the Mamaland model and suggests that the problem lies not in conservation itself but in the institutional conditions under which it is implemented. The authors also document forms of community resistance, from deliberate non-compliance with access restrictions to vocal opposition at meetings and social ostracism of perceived collaborators.

Looking forward, the researchers call for a foundational shift toward radical land tenure security, community-led forest governance, and agroecological perspectives that treat agricultural production and forest conservation as complementary rather than oppositional objectives. They propose that any future conservation investment be assessed against threshold questions: whether it respects existing governance structures, whether benefit-sharing terms are publicly disclosed and legally enforceable, whether communities hold genuine decision-making authority beyond mere consultation, and whether viable alternatives to displaced livelihoods are provided. Investments failing to satisfy all four criteria should be subject to heightened scrutiny. The stakes could not be higher, as the 40-year lock-in of the Mamaland concession means decisions made today will shape Malawian forests and livelihoods until 2066. Whether this legacy is judged as climate leadership or carbon colonialism depends on actions taken in the immediate window to retrofit transparency, accountability, and genuine inclusion into agreements that remain dangerously opaque.

Subject of Research: The socio-ecological impacts and governance failures of conservation concessions as a form of green grabbing in the Global South

Article Title: Conservation concessions or green grabbing? A critical perspective on mega conservation investments

Article References: Makwinja, Y. H., & Makare, B. (2026). Conservation concessions or green grabbing? A critical perspective on mega conservation investments. Frontiers in Sustainable Resource Management, 5, Article 1819454. https://doi.org/10.3389/fsrma.2026.1819454

Image Credits: AI Generated

DOI: 10.3389/fsrma.2026.1819454

Keywords: green grabbing, conservation concessions, carbon credits, land rights, Malawi, critical agrarian studies, forest governance, rural livelihoods, neoliberal conservation, dispossession, REDD+, political economy

The team approached the question not by asking who holds legal authority on paper, but by tracing who actually talks to whom, cooperates with whom, and depends on whom. Using social network analysis, a method borrowed from sociology that treats organizations and groups as nodes and their working relationships as edges, the researchers constructed a map of stakeholder interaction in and around Gargeda State Forest. The resulting network contains 27 nodes and 55 edges, a moderately sparse structure with a network density of 0.156. In practical terms, that density figure means only about sixteen percent of all possible relationships among the actors actually exist. For a forest whose survival depends on coordinated action, the authors argue, that sparseness is itself a finding: many stakeholders who could be cooperating simply are not.

The composition of the network is where the power imbalance becomes stark. Government institutions account for 66.7 percent of all nodes, meaning two out of every three actors in the governance system are state bodies. These institutions drive policy formulation, control resource allocation, and dominate decision-making. Local social groups, the people who live closest to the forest and interact with it daily, make up just 18.5 percent of the network, contributing primarily through community-based management activities. Non-governmental organizations occupy the remaining 14.8 percent, and the study characterizes their role as intermediaries, bridging grassroots actors and policymakers. This distribution echoes a long-running debate in environmental governance scholarship, rooted in Elinor Ostrom’s foundational work on governing the commons, about whether top-down state control or polycentric, community-anchored arrangements deliver better outcomes for shared natural resources.

But counting nodes only tells part of the story. The researchers also analyzed the strength of each relationship, classifying the 55 edges into four tiers. Moderate ties, rendered in pink in the network visualization, constitute 57.9 percent of all connections with a weight of 2, and the study describes them as the operational backbone of the governance system, the everyday working relationships that keep routine management functioning. Strong ties, shown in green, represent 13.8 percent of edges with a weight of 3, indicating substantial cooperation between the actors involved. Weak ties, in purple, account for 12.8 percent with a weight of 1, and these are the connections the authors flag as requiring reinforcement, relationships that exist nominally but carry little collaborative substance. At the top of the scale, the strongest ties, shown in blue, make up 15.5 percent of edges with a weight of 4, reflecting deeply integrated partnerships and shared leadership.

That tiered structure carries a diagnostic message. A healthy collaborative governance network, according to much of the literature the study draws upon, needs a solid core of strong, trust-based relationships surrounded by enough moderate and weak ties to circulate information and bring new actors into the conversation. Gargeda’s network has the right shape in one sense, since the majority of its ties are operational rather than superficial, but the relatively small proportion of deeply integrated partnerships suggests that genuine power-sharing and joint leadership remain the exception rather than the rule. Where the strongest ties do exist, they represent exactly the kind of shared decision-making that collaborative forest management frameworks aspire to, and the study treats them as a model for what the rest of the network could become.

The analysis was carried out with Gephi 0.10.1, an open-source network visualization and analysis platform widely used across the social sciences. Mapping the network in this way does more than produce an attractive diagram; it allows researchers to identify which actors sit at structural bottlenecks, which connections are fragile, and where a single failure could fragment the whole system. In Gargeda, the visualization made one vulnerability especially visible: over-reliance on central actors, with REDD+, the international framework for reducing emissions from deforestation and forest degradation, singled out as a hub whose outsized position creates risk. If a central node weakens or withdraws, the actors connected only through it can lose their channels of coordination entirely, a phenomenon network scientists call structural vulnerability.

The study also documents the practical frictions that constrain effective governance in the region. Inadequate infrastructure limits the ability of institutions and communities to meet, monitor, and enforce management plans across the forest landscape. Political instability disrupts the continuity that long-term forest management requires, since programs and personnel can be interrupted by shifts in the wider governance environment. These logistical challenges are not unique to Gargeda; comparative studies from Ghana, Vietnam, Indonesia, and Tanzania cited in the research describe similar patterns in which well-designed collaborative frameworks stall against the realities of underfunding, weak local capacity, and shifting political priorities. What the Ethiopian case adds is a precise, quantitative measure of how those pressures translate into the architecture of the stakeholder network itself.

The authors’ recommendations follow directly from the network evidence. They call for integrating traditional and formal governance systems, a theme that resonates with recent research on the Ethiopian-Kenyan borderlands showing that customary and state institutions can complement rather than compete with each other in environmental resource management. They advocate enhancing decentralized leadership so that decision-making authority is not concentrated in distant government offices, and strengthening stakeholder collaboration to raise the network’s density and deepen its weakest ties. Inclusive decision-making, infrastructure development, and capacity building are identified as the three levers most likely to produce a more sustainable and equitable governance model for the protected natural forest. Each recommendation targets a specific structural weakness the analysis exposed: low density, thin community representation, and fragile dependence on central hubs.

Why should readers far from western Ethiopia care about a 27-node network in one state forest? Because the Gargeda study demonstrates a method that can be applied anywhere contested natural resources are managed by many hands. Climate change is raising the stakes for forest governance worldwide, with research showing growing risks to forests from warming temperatures and mounting pressure on tropical forest nations to deliver both conservation and development. Whether collaborative governance succeeds in places like Gargeda will help determine whether forests continue to store carbon, shelter biodiversity, and sustain rural livelihoods. By converting the messy reality of stakeholder politics into measurable structure, density, tie strength, and centrality, the study gives practitioners a tool for diagnosing governance failures before they become ecological ones. The trees of Gargeda State Forest, in other words, are being governed by a network, and for the first time that network has been made visible, measured, and opened to deliberate redesign.

Subject of Research: Collaborative forest governance and stakeholder network analysis in Gargeda State Forest, western Ethiopia

Article Title: Institutional Arrangements and Collaborative Forest Governance in Gargeda State Forest, Western Ethiopia

Article References: Telila, Z., Amare, A., & Tolera, T. (2026). Institutional Arrangements and Collaborative Forest Governance in Gargeda State Forest, Western Ethiopia. Environmental Management, 76(10), Article 334. https://doi.org/10.1007/s00267-026-02641-8

Image Credits: AI Generated

DOI: 10.1007/s00267-026-02641-8

Keywords: forest governance, social network analysis, Ethiopia, collaborative management, REDD+, stakeholder collaboration, community-based forest management, institutional arrangements, Environmental Management, deforestation, Gephi, natural resource governance

The study builds on the nexus perspective, which treats biodiversity, water, food, health, and climate as coupled systems rather than separate policy silos. Within this framing, interlinkages describe influences among elements, interdependencies arise when one element depends on another to function, synergies occur when improvement in one element enhances another, and trade-offs occur when improvement in one worsens another. The Intergovernmental Panel on Climate Change has identified climate change as a threat multiplier that deepens existing vulnerabilities in societies shaped by inequality and institutional fragility. Intact ecosystems moderate climatic extremes, regulate hydrological cycles, sustain food production, and protect human health, while degradation weakens these buffering functions and heightens exposure. The authors argue that recognizing this interdependence has not yet produced sufficiently integrated climate action, because mitigation pathways remain misaligned with long-term temperature goals and adaptation measures often lack institutional coherence.

The comparative results reveal three striking patterns. First, ecosystem-centered and demand-side options exhibit the strongest cross-nexus synergies. Agroecology, wetland conservation and restoration, forest-based practices, coastal and marine ecosystem restoration, and sustainable healthy diets show predominantly positive biodiversity-food interactions alongside consistent gains in water regulation and health. Increasing soil organic carbon shows a similar profile, although the permanence of sequestration remains a recognized constraint. Second, infrastructure- and technology-centered mitigation options display more differentiated outcomes. Offshore wind power and land-based solar photovoltaics deliver clear mitigation and health gains through decarbonization and reduced air pollution, but their biodiversity and food-system interactions vary with marine ecosystem disturbance and competition for land. Third, system-enabling options such as multi-hazard early warning systems and reductions in short-lived climate pollutants generate mediated but important effects, with global cooperation for finance and technology functioning as a structural enabler across all domains.

Across every category, trade-offs cluster around land competition, biomass demand, tenure and access rights, affordability, and distributional equity. The authors emphasize that mixed outcomes do not imply net failure; rather, they reveal structural tensions within socio-ecological systems that must be governed rather than ignored. The analysis then applies a second evaluative layer, scoring each option for compatibility with Earth System Justice, a framework that treats distributive equity, procedural fairness, intergenerational responsibility, and recognition of diverse knowledge systems as constitutive elements of planetary governance. Agroecology, forest-based practices, coastal restoration, and sustainable healthy diets score highest on both justice compatibility and nexus governance synergy, while solar and wind power score moderately, reflecting the fact that distributive outcomes hinge on siting, tenure, and benefit-sharing design rather than on technological maturity itself.

To test these mechanisms in the real world, the team traced five enabling-condition cases in depth. In Andhra Pradesh, India, community-managed natural farming reported enhanced agrobiodiversity, improved groundwater recharge, increased dietary diversity, and reduced agrochemical exposure. Agronomic technique alone does not explain these gains. The Rythu Sadhikara Samstha platform connected state agencies with self-help groups, farmer networks, and civil society organizations, decentralizing authority while maintaining coordination, and enabling farmer-led experimentation through field schools. Women farmers and marginal groups were actively included, and synergies stabilized precisely where distributive equity, recognition of local knowledge, and cross-sectoral coordination converged. The case demonstrates that institutional architecture, not merely soil science, determines whether ecological practices translate into system-wide benefits.

Indigenous-led REDD+ initiatives in the Brazilian Amazon tell a parallel story about tenure security. Documented outcomes include avoided deforestation, habitat protection, strengthened watershed function, and reduced fire-related health burdens, with food systems benefiting through continued access to non-timber forest products. Where customary land rights were formally recognized and indigenous institutions retained authority, mitigation aligned with livelihood security. The Amazon Fund linked Indigenous Peoples and local communities, non-governmental organizations, and state agencies within a multi-level governance architecture, while participatory mapping and satellite monitoring integrated scientific tools with indigenous knowledge. Crucially, where communities were treated as beneficiaries rather than rights-holders, conflict and instability followed. Carbon finance without recognition justice, the authors conclude, does not secure durable cross-nexus outcomes.

Further evidence comes from Kenya, where the Mikoko Pamoja initiative links mangrove rehabilitation to community development. Carbon revenues finance education and water infrastructure, and the project operates through community-state-donor co-management with transparent revenue governance and negotiated trade-offs between conservation and livelihoods. In Medellín, Colombia, urban green corridors expanded tree cover, improved air quality, reduced heat exposure, and delivered measurable mental and cardiovascular health benefits, though spatial inequities in access persisted and green gentrification posed risks to vulnerable populations. In Wayanad, India, the revitalization of local diets and health traditions revived wild edible species, strengthened food sovereignty, and improved dietary quality through more than five hundred training sessions connecting indigenous knowledge holders with scientific institutions. By contrast, the Kachung Forest Project in Uganda serves as a contested counter-case: despite formal Clean Development Mechanism certification, contested degradation baselines, restricted access to land, fuelwood, and grazing areas, and limited recognition of customary resource use undermined its legitimacy, showing that carbon accounting cannot compensate for weak procedural inclusion.

The governance analysis identifies two complementary institutional models. Polycentric governance distributes authority across multiple, overlapping centers of decision-making, supporting experimentation, adaptive learning, and context-sensitive responses, with redundancy across centers enhancing resilience. Yet decentralization without coordination may reproduce sectoral silos and existing power asymmetries, or enable elite capture. Nexus governance addresses this weakness by making explicit the interdependencies across biodiversity, water, food, health, and climate, resting on five principles from the IPBES Nexus Assessment: integrative and transdisciplinary framings, inclusive engagement, explicit attention to justice and accountability, cross-scale coordination, and adaptive, reflexive governance. Financial and technological arrangements act as structural filters across all options, with limited concessional finance, high debt burdens, and risk-averse investment restricting implementation in many low- and middle-income settings, while harmful subsidies for fossil fuels, agriculture, forestry, and fisheries divert resources from renewable and circular pathways.

The authors are careful to acknowledge limitations. The study uses ordinal scoring and qualitative mechanism tracing rather than statistical causal identification, and cannot estimate average treatment effects or universal rankings. Evidence coverage varies across options, regions, and institutional settings, and the expert assessment did not employ blinded independent coding or formal sensitivity analysis. The findings should be read as evidence-supported comparative tendencies rather than deterministic predictions, and the authors call for future research using preregistered systematic review, independent parallel coding, and quantitative sensitivity analysis. Even so, the central inference stands: technical potential alone cannot explain uneven co-benefits across connected systems. Durable outcomes become plausible when institutions coordinate across sectors and scales, distribute benefits and burdens fairly, enable meaningful participation, respect plural knowledge systems, and maintain accountable long-term finance. Climate responses, the study argues, should be evaluated through both their direct effects and the institutional conditions governing their persistence, aligning ecological interdependence with rights, responsibilities, and public accountability.

Subject of Research: Nexus governance and Earth System Justice conditions shaping co-benefits of climate response options across biodiversity, water, food, and health

Article Title: Enabling climate action: A nexus approach for delivering co-benefits across biodiversity, water, food, and health

Article References: Singh, P. K., Gupta, H., Díaz-José, J., McElwee, P. D., Tirado, M. C., Cherubini, F., Duchková, H., Llope, M., Vale, M. M., Khan, S., Ito, A., Hori, M., Eriksen, S. H., Tiwari, L., Phang, S. C., Mason-D’Croz, D., Xu, X., van Huysen, T., Herrero, M., … Smith, P. (2026). Enabling climate action: A nexus approach for delivering co-benefits across biodiversity, water, food, and health. iScience, 29(11), Article 117734. https://doi.org/10.1016/j.isci.2026.117734

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117734

Keywords: climate change, nexus approach, biodiversity, water, food security, public health, IPBES, Earth System Justice, governance, agroecology, REDD+, indigenous knowledge

The research, led by Dhia Zalfa Zahira, Anjar Dimara Sakti, and Ketut Wikantika of Institut Teknologi Bandung, goes beyond simply counting lost trees. It tracks how much carbon those forests actually stored — both above ground in trunks, branches, and leaves, and below ground in root systems — and how that storage changed year by year. Most previous studies of the region offered static snapshots for a single year or focused only on aboveground biomass. By modelling both aboveground and belowground biomass carbon across five time points, the team has produced one of the most dynamic pictures yet of a tropical carbon reservoir in decline.

Defining what counts as an intact forest was itself a technical feat. The researchers started with the Hansen tree cover dataset derived from Landsat imagery, flagging any pixel with at least 30 percent canopy cover in 2000. They then filtered out oil-palm plantations using a global planting-year dataset and removed cropland using the MODIS land cover product. From that baseline, they iteratively subtracted three drivers of loss — stand-replacing deforestation, new cropland, and new oil-palm planting — at five-year intervals, generating intact forest maps for 2000, 2005, 2010, 2015, and 2020. This multi-layer filtering matters because oil-palm plantations, though tree-covered, are not ecologically intact forests; they typically replace natural forest and store far less carbon.

With the forest maps in hand, the team turned to a Random Forest regression model, an ensemble machine learning method that aggregates predictions from hundreds of decision trees. Thirteen environmental predictors fed the model, spanning vegetation indices such as NDVI and NIRv, productivity metrics including gross and net primary productivity, leaf area index, and the fraction of absorbed photosynthetically active radiation, along with climate variables like land surface temperature and precipitation, and topographic features including elevation, slope, and a topographic wetness index. All layers were processed at 300-metre resolution and aggregated to 1.5-by-1.5-kilometre grids to reduce noise and pixel misalignment.

A key design choice set this model apart: rather than training only on forest pixels, the researchers trained across the full gradient of Southeast Asian vegetation — forests, shrublands, grasslands, and cropland alike — using more than two million grid cells from 2010. This ensures the model learned the entire spectrum of carbon density, reducing bias at forest edges and recently disturbed areas. The data was split 80-20 into training and testing sets, with a Kolmogorov-Smirnov test confirming that both subsets covered the region geographically without spatial bias. Against the NASA reference biomass dataset, the model achieved a testing R² of 0.899 for aboveground carbon and 0.874 for belowground carbon, indicating strong predictive skill with limited overfitting.

Independent validation against the European Space Agency’s Climate Change Initiative Biomass product — built from radar observations by Sentinel-1, Envisat, and the ALOS satellites — showed moderate but consistent agreement, with R² values of 0.645 and 0.632 for the two carbon components. Among the thirteen predictors, the fraction of absorbed photosynthetically active radiation emerged as the single most influential variable, which makes physical sense: how much solar energy a canopy captures directly governs how much carbon it can fix into biomass. Land surface temperature and precipitation followed, while the classic vegetation indices contributed surprisingly little, apparently limited in their sensitivity to structural biomass in dense tropical canopies.

The carbon accounting that followed is sobering. In 2000, intact forests in the region held an estimated 26.18 megatonnes of aboveground biomass carbon and 6.61 megatonnes belowground, a combined total of roughly 32.8 megatonnes. By 2020, those figures had fallen to 15.96 and 3.96 megatonnes respectively — a drop of more than 39 percent in twenty years. The steepest losses occurred between 2010 and 2015, when forest area shrank by nearly 384,000 square kilometres and biomass carbon declined at a rate of about 1,496 megatonnes per year in total. The hardest-hit landscapes were Kalimantan and Sumatra in Indonesia, Sarawak and Sabah in Malaysia, and cropland-driven loss zones in northern Thailand, Myanmar, and parts of Papua.

To translate those ecological losses into terms policymakers cannot ignore, the team ran an indicative economic valuation under two carbon pricing scenarios. At the current average price across ASEAN+3 countries — a modest 6.45 US dollars per tonne of CO₂ equivalent — the region’s intact forest carbon was worth about 776 billion dollars in 2000, falling to roughly 471 billion by 2020. Under the globally recommended price of 75 dollars per tonne, aligned with social cost of carbon estimates, the value dropped from about 9.02 trillion dollars to 5.48 trillion. The authors are careful to stress these are illustrative, non-market figures, not credit-eligible carbon trading values, but they make the scale of the liability unmistakable: a loss of nearly 4 trillion dollars in indicative carbon assets in two decades.

The findings land at a delicate moment for climate policy. Southeast Asia harbours nearly 15 percent of the world’s tropical forests, and their continued erosion threatens not only regional biodiversity but global mitigation commitments under the Paris Agreement, REDD+ frameworks, and Sustainable Development Goal targets on sustainable forest management. There is also a real risk of a tipping dynamic: as intact forests degrade, they can flip from carbon sinks to net carbon sources, emitting more than they absorb and accelerating the very warming that stresses them. The spatially explicit maps produced by this study could help governments prioritise conservation zones where avoided deforestation yields the greatest climate benefit, and design community-based forest management schemes that recognise indigenous peoples as the primary stewards of these carbon reservoirs.

The study is candid about its limitations. The 2000 baseline may include some old plantations that the Hansen dataset cannot distinguish from natural forest; the model assumes predictor relationships stable across two decades; and the absence of explicit spatial block cross-validation means the reported accuracy figures may be somewhat optimistic. The economic valuation, by design, omits additionality, leakage, and monitoring requirements. Still, the core signal — a 59 percent collapse in intact forest area and a 39 percent loss of biomass carbon, tracked with low reported uncertainty — is difficult to dispute. Future work integrating radar-based biomass data and country-specific carbon accounting could sharpen the picture further. What this study makes clear is that Southeast Asia’s intact forests are not merely an ecological treasure; they are a quantifiable, and rapidly depreciating, planetary asset.

Subject of Research: Remote sensing and random forest modelling of intact forest biomass carbon dynamics and carbon economics in Southeast Asia from 2000 to 2020

Article Title: Intact forest carbon dynamics and indicative carbon economy in Southeast Asia: A remote sensing and random forest approach

Article References: Zahira, D. Z., Sakti, A. D., & Wikantika, K. (2026). Intact forest carbon dynamics and indicative carbon economy in Southeast Asia: A remote sensing and random forest approach. Environmental Advances, 26, Article 100758. https://doi.org/10.1016/j.envadv.2026.100758

Image Credits: AI Generated

DOI: 10.1016/j.envadv.2026.100758

Keywords: intact forests, Southeast Asia, biomass carbon, remote sensing, random forest, deforestation, oil palm, carbon pricing, REDD+, aboveground biomass, belowground biomass, machine learning

The research, published in Discover Forests by Niamjit Das of Shahjalal University of Science and Technology and Md. Qumruzzaman Chowdhury, examined three of the most widely planted timber taxa in South and Southeast Asia: Acacia auriculiformis, Acacia mangium, and the interspecific hybrid between them. Working across ten plantation sites in Sylhet Division, a humid monsoon landscape receiving roughly 5,000 millimeters of rain each year, the team measured 1,050 trees spanning ages of 8 to 15 years and stand densities of 1,100 to 1,400 trees per hectare. Crucially, they did not stop at tape measurements. They felled 75 trees, 25 of each taxon, cut the stems into sections, and dried them in ovens at 105 degrees Celsius until their weight stopped changing, producing the kind of ground-truth biomass data that allometric modeling depends on.

The central finding is that stump diameter, measured just 30 centimeters above the ground, predicts breast-height diameter almost perfectly. A simple log-log regression achieved adjusted R-squared values exceeding 0.98 across all three taxa, with root mean square errors as low as 0.048. In practical terms, this means a forester walking through a recently harvested compartment can measure the remaining stumps and reconstruct the diameter distribution of the trees that once stood there with negligible error. The relationship makes intuitive biological sense: the base of the stem and the breast-height section are connected by the tree’s taper, and within a given species and growth environment that taper follows a consistent geometric pattern.

Biomass prediction proved nearly as strong. Stump-based models performed comparably to the conventional DBH-based equations, with the parsimonious log-log stump model reaching adjusted R-squared values between 0.945 and 0.968 for stem biomass. The authors were careful to emphasize validation statistics rather than goodness-of-fit alone, a discipline that forest scientists have repeatedly called for after decades of unreliable generic equations being applied across unrelated ecosystems. Observed and predicted values clustered tightly around the one-to-one line, paired t-tests found no significant bias, and residuals were balanced across the size spectrum. For the hybrid Acacia, mixed-effects models that accounted for random variation among species and sites reduced prediction bias even further.

The study also put machine learning to the test, and the results offer a cautionary tale for the current enthusiasm surrounding artificial intelligence in environmental science. Random Forest, an ensemble method that averages hundreds of decision trees, consistently identified stump diameter as the strongest predictor of stem biomass and produced stable, generalizable predictions under five-fold cross-validation. Gradient Boosting, by contrast, assigned the highest relative importance to DBH and showed a telltale 12 percent gap between training and validation accuracy, the classic signature of overfitting. The authors are refreshingly candid about what this means: stump diameter’s dominance in the Random Forest reflects its strong correlation with overall tree size, not some newly discovered biological law, and variable importance rankings can shift with model settings and data structure.

Converting biomass into carbon introduced a species-specific dimension that generic accounting often misses. Rather than applying the default IPCC carbon fraction, the researchers used conversion factors drawn from published Acacia studies: 0.475 for A. auriculiformis, 0.480 for A. mangium, and 0.485 for the hybrid, reflecting real differences in wood chemistry among the taxa. The resulting carbon stock estimates ranked the hybrid Acacia highest, followed by A. mangium and then A. auriculiformis, a pattern consistent with the hybrid’s reputation for superior growth and wood quality. The authors stress that these figures cover stem carbon only, excluding branches, foliage, and roots, and therefore should not be read as total ecosystem carbon stocks.

The methodological rigor underlying these numbers deserves attention. Measurements were restricted to the dry season to minimize moisture-related variability, instruments were calibrated daily, and any readings differing by more than 0.5 centimeters in diameter or 0.2 meters in height triggered re-measurement. Oven-drying continued for 48 to 72 hours with weights checked at 12-hour intervals, and data entry was cross-checked by two independent researchers. The validation design was two-tiered: 975 trees held back from model development served as an independent test set, and five-fold cross-validation stratified by species and site confirmed that the models were not merely memorizing the quirks of particular plantations. This is precisely the kind of quality assurance that earlier reviews of forest biomass estimation have found lacking in much of the published literature.

Why does this matter beyond Bangladesh? Tropical forests hold nearly a third of terrestrial carbon, and programs such as REDD+ depend on credible, verifiable measurements of how much carbon is stored and, crucially, how much is removed when trees are harvested. Under current practice, post-harvest carbon accounting is notoriously difficult because the trees that would provide the measurements are gone. Stump-based equations change that calculus entirely: the stumps remain in the ground, they are easy to locate and measure, and they now carry enough information to reconstruct the stand’s biomass and carbon content. The authors note that this capability could inform measurement, reporting, and verification frameworks under REDD+ and support IPCC Tier 2 and Tier 3 approaches, though they are careful to say that broader policy applications require independent validation.

The limitations are stated with unusual honesty. The study covered healthy trees in even-aged Acacia plantations on fertile alluvial loams in a single region; damaged or suppressed trees were excluded, which may limit applicability in operational forestry where such trees are common. Buttressed stems and mixed-species stands remain challenging, and the models were calibrated on trees aged 8 to 15 years, so extrapolation to older rotations or different environments is untested. The improvements offered by mixed-effects and machine learning approaches, while statistically significant, were described as modest in operational terms, and the authors insist that DBH remains the conventional standard with stump diameter serving as a complementary surrogate rather than a replacement.

Even with those caveats, the study delivers something tropical forestry has needed for a long time: a cheap, fast, and demonstrably accurate way to audit carbon in the places where conventional measurement fails. As plantation forestry expands across the tropics to meet timber demand and climate goals under SDG 13 and SDG 15, the ability to turn a field of cut stumps into a credible carbon ledger could reshape how harvest impacts are monitored and reported. The next step, the authors argue, is testing these equations across wider environmental gradients, diverse plantation ages, and mixed-species stands, and incorporating belowground biomass into the accounting. Until then, the message to foresters and carbon accountants is clear: do not overlook the stump, because it remembers everything the tree knew.

Subject of Research: Stump diameter as a predictor of biomass and carbon stocks in tropical Acacia plantations in Bangladesh

Article Title: Stump diameter is a robust predictor of biomass and carbon stocks in tropical Acacia plantations

Article References: Das, N., & Chowdhury, M. Q. (2026). Stump diameter is a robust predictor of biomass and carbon stocks in tropical Acacia plantations. Discover Forests, 2(1), Article 73. https://doi.org/10.1007/s44415-026-00137-1

Image Credits: AI Generated

DOI: 10.1007/s44415-026-00137-1

Keywords: stump diameter, biomass estimation, carbon stocks, Acacia plantations, allometric models, REDD+, Bangladesh, machine learning, mixed-effects models, forest mensuration, destructive sampling, carbon accounting

The research, led by Binayak Poudel of the Institute of Forestry at Tribhuvan University, together with colleagues in Canada and Nepal, quantified both vegetation carbon and soil organic carbon across three dominant forest types: Shorea robusta (sal), Pinus roxburghii (chir pine), and mixed broadleaved forests. Working in two community forests in Kaski District—the 162-hectare Sityum Kasyari and Simsar Patleswara Jukepani Community Forest and the 14-hectare Banpale Community Forest—the team established nineteen nested circular plots of 500 square meters each, measuring every tree with a diameter at breast height of at least five centimeters. Soil samples were collected from four depth intervals reaching down to 80 centimeters, with five subsamples composited at each depth to smooth out local heterogeneity.

The results were striking. Shorea robusta forests emerged as the undisputed carbon champions, storing 113.5 plus or minus 7.1 megagrams of carbon per hectare in vegetation and 102.0 plus or minus 2.3 megagrams per hectare in soil—substantially more than chir pine forests, which held 96.5 and 85.5 megagrams respectively, and far ahead of mixed broadleaved forests at just 64.2 and 84.9 megagrams. Together, the sal forests banked roughly 215 megagrams of carbon per hectare across vegetation and soil combined, placing them at the upper end of the range reported for South Asian subtropical forests.

But the real analytical payoff came from teasing apart why these differences exist. The researchers evaluated fourteen predictors spanning stand structure, anthropogenic disturbance, soil properties, topography, and climate, using Pearson correlation analysis and principal component analysis to identify the dominant drivers. For tree carbon, two structural variables towered above the rest: basal area, with a correlation coefficient of 0.641, and canopy cover, at 0.635, both highly significant. Tree height and stem density, by contrast, showed only weak, non-significant positive relationships—a reminder that a forest crowded with small stems stores far less carbon than one anchored by a few massive trunks.

Equally important was what the analysis revealed about human pressure. The team constructed an Anthropogenic Disturbance Index combining stem cutting, leaf litter collection, lopping intensity, and fire influence, each weighted equally. This index correlated negatively with tree carbon at r equals minus 0.60, a statistically significant signal that where people extract biomass, carbon stocks suffer. Mixed broadleaved forests, which local communities depend on most heavily for fuelwood and cattle fodder, showed the highest disturbance levels and the lowest carbon stocks. Chir pine forests, whose needles are unsuitable for composting or fodder, experienced the least disturbance.

Soil organic carbon told a different story entirely. Here, the strongest correlate was not a property of the trees but a property of the ground itself: soil texture. Silt content correlated positively with SOC at r equals 0.587, while sand content showed a significant negative correlation at r equals minus 0.581. This pattern reflects a well-established mechanism in soil science—fine mineral particles form stable organo-mineral complexes that physically shield organic matter from microbial decomposition, whereas sandy soils, with poor aggregate structure and low water retention, accelerate mineralization. Canopy cover was the only structural variable significantly associated with soil carbon, at r equals 0.560, suggesting that dense canopies moderate soil temperature and moisture in ways that favor organic matter accumulation.

Principal component analysis confirmed this division of labor. For tree carbon, the first two principal components explained 53.2 percent of total variance, with carbon clustering alongside basal area, canopy cover, and stem density. For soil carbon, the first two components accounted for 52.8 percent of variation, dominated by textural and site variables. Permutational multivariate analysis of variance showed that forest type explained 45 to 46 percent of the variation in both pools—statistically significant for each. Intriguingly, elevation correlated negatively with soil carbon while aspect correlated positively with tree carbon, and mean annual temperature showed a positive relationship with SOC that the authors attribute to the co-distribution of warmer, more productive lower-elevation sal forests rather than a direct climatic effect.

The comparison with earlier Nepalese and Himalayan studies adds valuable context. Previous work in Makawanpur district reported sal forest biomass as high as 313.69 megagrams per hectare in well-managed community forests, while degraded stands in Dang district stored barely 99 megagrams. Protected-area studies in Shuklaphanta National Park found core-zone carbon stocks of 258.56 megagrams per hectare versus 193.3 in buffer zones—a protected-area effect that mirrors the disturbance gradient documented in the new study. The authors also note that Nepal’s total forest topsoil SOC has been estimated at 494 million tons, a figure that local-scale studies like this one help refine for national inventories.

The study is candid about its limitations. Nineteen plots distributed unevenly across three forest types constrain statistical power, and the geographic scope of two community forests in a single district limits extrapolation. The analysis relies on correlation and PCA, which identify associations without establishing causality, and the disturbance index applies equal weights to pressures that likely differ in carbon impact. Climate data at 1-kilometer resolution from WorldClim varied too little across plots to serve as strong predictors, and the fieldwork captured only a single post-monsoon season. The authors recommend denser plot networks, structural equation modeling, soil carbon fractionation, and longer observation windows in future work.

Yet the management implications are clear and actionable. Because basal area, canopy cover, and disturbance intensity are readily measurable in routine forest inventories, they can be embedded directly into community forest operational plans and carbon monitoring frameworks. Protecting large-diameter trees, maintaining canopy closure, and strictly regulating cutting, lopping, litter removal, and fire emerge as the highest-leverage interventions for maximizing ecosystem carbon. For Nepal’s REDD+ program and national carbon accounting, the message is that structural integrity—rather than forest type alone—should anchor carbon-oriented planning in the country’s community forests, which cover nearly 45 percent of the national land area and represent one of the developing world’s most celebrated conservation success stories.

Subject of Research: Carbon storage drivers in Nepalese mid-hill community forests

Article Title: Stand structure drives vegetation carbon storage while soil texture regulates soil organic carbon in Nepalese mid-hill community forests

Article References: Poudel, B., Bhattarai, S., Koirala, S., Chapagain, J., & Timilsina, S. (2026). Stand structure drives vegetation carbon storage while soil texture regulates soil organic carbon in Nepalese mid-hill community forests. Discover Forests, 2(1), Article 69. https://doi.org/10.1007/s44415-026-00130-8

Image Credits: AI Generated

DOI: 10.1007/s44415-026-00130-8

Keywords: forest carbon, soil organic carbon, stand structure, basal area, canopy cover, Shorea robusta, anthropogenic disturbance, soil texture, community forestry, Nepal, REDD+, carbon stocks

The research team, led by Anaelle Brunda Djiaha and Marlène Ngansop Tounkam of the University of Douala together with Philippes Mbevo Fendoung of the National Advanced School of Public Works in Yaoundé, built their analysis on Landsat satellite scenes captured in the dry-season months of February 2000, March 2010, December 2014, and January 2022. Choosing dry-season imagery was a deliberate technical decision: cloud cover in Cameroon’s wet season can obscure the ground and corrupt classification algorithms, so the researchers favored dates when visibility was near optimal. Each scene was assembled into multispectral composites, radiometrically corrected to convert raw digital numbers into surface reflectance, and classified using the Maximum Likelihood algorithm, a supervised method that assigns each pixel to the land cover class it statistically most resembles. Five classes emerged: mature highland forest, medium-aged secondary forest, shrub savannah, agrosystems, and built-up areas.

The rigor of this classification was validated on two fronts. Confusion matrices built from thousands of reference points, ranging from 3,215 samples in 2000 to more than 31,000 in 2022, yielded Kappa coefficients between roughly 0.93 and 0.99 across all four dates, well above the 0.85 threshold generally accepted as indicating strong agreement between classified and reference data. On the ground, the team surveyed more than 110 GPS-truth points over 20 days of fieldwork, correcting misclassified pixel blocks and confirming which land cover categories were genuinely present. This dual validation matters because the entire downstream analysis, from change-detection matrices to carbon accounting, rests on the accuracy of those classifications.

The temporal story that emerges is dramatic. In 2000, high-altitude forest covered 66 percent of the reserve, roughly 6,199 hectares, with secondary forest at 13 percent, savannah at 15 percent, and agriculture and settlement each at 3 percent. By 2010 the mature forest share had slipped to 63 percent, but the steepest decline came in just four years: between 2010 and 2014, highland forest plummeted from 5,932 to 3,693 hectares, an annual loss of more than 570 hectares, while medium-aged secondary forest nearly doubled as degraded and regenerating land replaced old-growth canopy. By 2022, mature forest covered only 38 percent of the reserve, agrosystems had surged from 6 to 14 percent, and built-up areas had climbed to 5 percent, more than doubling from 136 to 456 hectares in just eight years. Transition matrices confirm the scale of conversion: over the full 22-year period, more than 6,000 hectares of land shifted out of secondary forest trajectories and over 1,250 hectares of mature forest were converted to other uses.

To understand what is driving this transformation, the researchers combined remote sensing with field observation and interviews. The verdict was unambiguous: agriculture accounts for 46 percent of degradation, human occupation for 34 percent, illegal logging for 14 percent, and bushfires for the remaining 6 percent. The reserve is surrounded by villages inhabited primarily by Mbo’o and Bamiléké communities whose livelihoods depend on cash crops such as cocoa, coffee, and oil palm as well as food crops like maize and cassava. A 20-kilometer secondary road linking Foumban to Bale has intensified access and anthropization, while selective artisanal sawmilling and slash-and-burn clearing accelerate the fragmentation. Elephants and panthers have already vanished from the reserve; the remaining wildlife, including primates, pangolins, aulacodes, and monitor lizards, now survives in an increasingly perforated habitat.

Beyond mapping change, the study quantified what this forest still stores in climate terms. Using established allometric equations for Cameroon’s tropical moist forests, the team measured every tree in 30 square plots of 30 by 30 meters distributed across the vegetation types, converting diameter and wood density into aboveground biomass, then into carbon using the standard 0.47 conversion fraction. The reserve’s overall carbon rate came to 0.874 tonnes of carbon per hectare, with medium-aged secondary forests standing out as the strongest carbon sinks at 0.534 tC/ha, followed by highland forest at 0.280 tC/ha. Agrosystems stored a negligible 0.002 tC/ha. The authors note candidly that these values are well below the 30 to 50 tC/ha typically reported for tropical secondary forests, attributing the gap to advanced degradation, plot representativeness, and extrapolation uncertainty, and they cross-validated their spatial carbon maps with an R-squared of 0.78 and a margin of error of roughly plus or minus 15 percent.

Perhaps the most consequential result is spatial: by overlaying the 2000 and 2022 forest classifications and subtracting what remained, the team identified 3,703 hectares, 53 percent of the entire reserve, as suitable for reforestation. These are zones where forest existed at the start of the century and no longer does, prime candidates for planting native species or assisted natural regeneration. If restored, the researchers estimate, this area could hold a carbon storage capacity of about 0.83 tC/ha, a meaningful contribution to both biodiversity recovery and climate mitigation in a region where protected areas are increasingly recognized as critical carbon reservoirs.

Looking forward, the team ran a CA-Markov cellular automata model in Idrisi Selva software, using transition probabilities derived from the historical record to simulate land cover in 2050. The projections, which the authors carefully frame as exploratory scenarios rather than predictions, suggest agricultural land expanding by 30 percent, built-up areas by 40 percent, and agroecosystems by 25 percent, primarily at the expense of remaining primary forest and savannah. The model rests on a stationarity assumption, that past trends will persist, which the authors acknowledge is vulnerable to disruption by policy shifts, land reform, or economic shocks, and they call for sensitivity analyses and hindcasting validation in future work. Even with those caveats, the trajectory is clear: without intervention, demographic and economic pressure will continue converting the reserve into farmland and settlements.

The policy implications extend well beyond one Cameroonian reserve. The authors argue that reversing these trends requires a comprehensive package: promoting sustainable agricultural practices, launching reforestation in the 3,703 hectares of priority zones, and, critically, involving local communities through training and participatory natural resource management. They point to evidence that REDD+ initiatives succeed best when payments for ecosystem services are coupled with local development programs such as agroforestry, and they stress the need for stricter land use regulations and the integration of conservation objectives into public policy. For a reserve whose very existence as a protected area is being tested by the communities that surround it, the path forward depends on aligning economic incentives with ecological survival, ensuring that Santchou’s remaining forests, and the carbon and biodiversity they harbor, are still standing in 2050.

Subject of Research: Forest cover dynamics, carbon stock assessment, and 2050 land use projections for the Santchou Wildlife Reserve in western Cameroon

Article Title: Forest dynamics and carbon stocks in the Santchou wildlife reserve from 2000 to 2022 and projections for 2050

Article References: Djiaha, A. B., Tounkam, M. N., & Fendoung, P. M. (2026). Forest dynamics and carbon stocks in the Santchou wildlife reserve from 2000 to 2022 and projections for 2050. Discover Conservation, 3(1), Article 28. https://doi.org/10.1007/s44353-026-00097-9

Image Credits: AI Generated

DOI: 10.1007/s44353-026-00097-9

Keywords: deforestation, forest degradation, carbon stocks, remote sensing, Landsat, Cameroon, protected areas, CA-Markov model, reforestation, REDD+, biodiversity conservation, land use change

The review, led by Shishir Chandrakar and Krishna Kumar Chandra of Guru Ghasidas Vishwavidyalaya together with Bhavana Dixit of Chhattisgarh Rajya Niti Aayog, is deliberately framed as a critical synthesis rather than a new empirical study. The authors screened more than 90,000 records from Web of Science, Scopus and Google Scholar, narrowing these through duplicate removal, title and abstract screening, and full-text assessment to a final pool of 223 publications meeting rigorous methodological criteria. The twenty-year window they define as long-term is not arbitrary: it spans four assessment cycles of the India State of Forest Report, covers the entire post-2005 period against which India’s Nationally Determined Contributions and forest-carbon pledges are tracked, and is long enough to capture slow processes such as soil organic carbon turnover and stand-level biomass accumulation that shorter studies simply cannot resolve.

The technical picture that emerges is one of enormous variability and genuine alarm. Aboveground biomass carbon in Central Indian forests fluctuated between 26.4 and 131.1 megagrams of carbon per hectare across the reviewed studies, while soil organic carbon stocks ranged from 24.6 to 50.2 megagrams per hectare. Total biomass in some landscapes reached 338.3 megagrams per hectare, and closed natural forests held considerably more carbon, around 208.22 megagrams per hectare, than open forests at roughly 95.11. Intact stands of mixed sal and teak performed best, and carbon stock densities across various forest types spanned roughly 50 to 180 megagrams per hectare, depending on tree density, species diversity, age structure and management history. These ranges matter because carbon accounting schemes, carbon markets and national inventories all depend on knowing how much carbon a given hectare actually stores.

What makes the findings striking is the disconnect they reveal between national aggregates and regional reality. Nationally, Indian forests remain recognised as vital carbon sinks, holding an estimated 7,124 million tonnes of carbon, and national reports recorded a net increase of 377 million tonnes of carbon between 1995 and 2005. Yet the granular, site-level evidence compiled in this review shows that vulnerable ecosystems in Central India are actively degrading and releasing carbon even as headline statistics improve. In one disturbed tropical forest landscape, approximately 1,851.8 hectares were lost between 2000 and 2020, largely to agricultural conversion, producing a net loss of 0.065 teragrams of biomass and roughly 59 gigagrams of carbon, equivalent to about 216 gigagrams of carbon dioxide. National averages, the authors argue, may be masking precisely the localised declines that matter most for conservation and climate policy.

The drivers of this carbon loss are neither mysterious nor singular. Deforestation driven by agricultural expansion, mining, urbanisation and infrastructure development remains the dominant force, but the review highlights a web of interacting pressures that together erode carbon stocks. Overgrazing suppresses regeneration and shifts species composition toward lower-biomass stands. Repeated low-intensity fires, many of them human-ignited, kill trees and reduce both biomass and soil carbon availability. Linear infrastructure such as roads and transmission lines fragments habitat and creates edge effects that elevate tree mortality and fire risk. Fuelwood extraction has a long history in the region, with an estimated deficit of 86 million tonnes recorded as far back as 1996, and excessive livestock grazing has stunted forest floor regeneration in around 67 percent of national parks and 83 percent of wildlife sanctuaries. Timber extraction alone accounted for roughly half of degradation in some studied landscapes, followed by fuelwood collection, fires and grazing.

Climate change is compounding, rather than replacing, these anthropogenic pressures. The Intergovernmental Panel on Climate Change projects global temperature rises of 1.5 to 4.5 degrees Celsius alongside doubled atmospheric carbon dioxide by the end of the century, and Central India sits squarely in the crosshairs. Vulnerability assessments rank Chhattisgarh, Madhya Pradesh and Odisha among the most climate-exposed regions in the country. Projections summarised in the review suggest that by 2050, large areas of tropical moist deciduous and semi-evergreen forest, covering some 520,280 square kilometres of India’s most dominant forest types, will fall within climatic hotspots, facing altered precipitation, elevated temperatures and increased drought and fire. Conflicting model scenarios add to the uncertainty: greenhouse gas forcing models predict warmer and wetter conditions that could boost productivity, while aerosol-inclusive models foresee drier, water-stressed futures that would accelerate the shift from moist to drier forest types.

Perhaps most unsettling is the evidence that extreme climate events can temporarily flip the sign of the regional carbon budget. During drought episodes, plant respiration in Central India’s deciduous forests has been documented to exceed primary productivity, releasing an estimated 210 million tonnes of carbon annually under those conditions. Drought-linked tree mortality accelerates decay-driven carbon release and raises fire probability, and El Niño-associated droughts globally amplify exactly this pattern. Soils, which hold the largest share of India’s forest carbon at over 50 percent of total stocks, are particularly exposed: decomposition rates respond directly to warming and shifting moisture, and the review notes a clear decline of soil organic carbon with depth, meaning topsoil degradation translates disproportionately into carbon loss.

The synthesis does not end on a purely pessimistic note, and its prescriptions are unusually concrete. Sustainable forest management, assisted natural regeneration of degraded lands, mixed-species planting with native species, soil moisture conservation, fire-line maintenance and invasive species control all emerge as proven levers for restoring carbon storage. India’s Nationally Determined Contributions target the sequestration of 2.5 to 3 billion tonnes of additional carbon dioxide and the restoration of 26 million hectares of degraded land by 2030, and the rehabilitation of degraded forests is estimated to offer a further 1,008.49 teragrams of carbon mitigation potential over 75 years. Species diversity itself matters: taxonomic richness and structural diversity correlate strongly with aboveground biomass through niche complementarity, and dominant regional species such as Diospyros melanoxylon, Butea monosperma and Shorea robusta are key carbon contributors. Monoculture plantations, by contrast, typically store less carbon and are more vulnerable to pests and climate extremes, a nuance the authors stress against simplistic area-based afforestation targets.

Community governance emerges as perhaps the decisive variable. Madhya Pradesh holds India’s largest forest area and second-largest carbon stock at 608 million tonnes, with Chhattisgarh close behind at 505 million tonnes, and both states sit at the heart of the Green India Mission and World Bank-supported Ecosystem Services Improvement Project. Chhattisgarh has been actively financing Community Forest Resource management plans developed by gram sabhas, the village assemblies empowered under the Forest Rights Act. Yet the review documents persistent friction: village councils often struggle to access funds because of complex administrative prerequisites and lingering resistance from state forest departments, while growing investment interest in forest lands for mining, carbon schemes and ecotourism raises concerns about pressure on Adivasi territories. The authors argue that genuine carbon mitigation in Central India hinges on authentic devolution of rights and finance to forest communities rather than on the scale of announced programmes.

Ultimately, the review positions Central India as both a warning and a test bed. The evidence for a region-wide shift to net carbon source status still rests on a limited number of regional studies rather than a dense monitoring network, and the authors are candid that belowground carbon dynamics remain under-sampled and methodological differences across studies complicate comparisons. But the direction of travel is clear enough that the distinction between national gains and regional losses cannot be ignored. Meeting India’s forest-carbon commitments, the synthesis concludes, will depend less on planting trees across aggregate areas and more on safeguarding the quality, species composition and soil integrity of existing natural forests in Chhattisgarh, Madhya Pradesh and Odisha. The authors call for harmonised long-term monitoring networks that integrate field inventories, remote sensing and soil carbon measurement, calibrated to Forest Survey of India assessment cycles. In a region where ecological sensitivity and socio-economic dependence on forests converge at their most intense, the next two decades will determine whether these landscapes slip further into carbon deficit or recover their role as durable climate allies.

Subject of Research: Twenty-year synthesis of forest carbon dynamics, stocks and sink-to-source transition in Central Indian tropical forests

Article Title: A critical synthesis of forest carbon dynamics in central india over two decades

Article References: Chandrakar, S., Chandra, K. K., & Dixit, B. (2026). A critical synthesis of forest carbon dynamics in central india over two decades. Discover Forests, 2(1), Article 64. https://doi.org/10.1007/s44415-026-00123-7

Image Credits: AI Generated

DOI: 10.1007/s44415-026-00123-7

Keywords: forest carbon dynamics, Central India, carbon sequestration, soil organic carbon, deforestation, REDD+, sustainable forest management, climate change, systematic review, India State of Forest Report, community forest rights, dry deciduous forests