Loader page.

Loader page.

Loader page.

Loader page.

Is Radware Cloud WAF down right now? Check the latest outage reports and share your experience. Get real-time alerts when Radware Cloud WAF is down.

We are sorry, an error has occurred... Contact our support service If there is an error with the site, please help us to improve our service by reporting the problem to our support team: customerservices@ioppublishing.org

Plus Radware counts real prompt injections aimed at GitHub triage bots, a TorchServe CVE nobody will fix, and patches for Junie and pypdf.

Published 12 November 2026 • © 2026 The Author(s). Published by IOP Publishing Ltd Environmental Research Letters, Volume 21, Number 21Citation Ben Filewod 2026 Environ. Res. Lett. 21 218002DOI 10.1088/1748-9326/aeb9f9 Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Daigneault, Sohngen, Belair, and Ellis 2025 (hereafter DSBE25) use a dynamic optimization model of the global timber sector (the Global Timber Model, or GTM) to estimate leakage from (roughly) biome-level mitigation interventions (10-year rotation extensions, permanent set-asides). Their results are designed for integration in forest carbon markets (which so far have lacked credible leakage accounting solutions) [1] and are seeing rapid uptake [2, 3]. The main message of DSBE25 is that leakage is much less of a problem than previously thought (SI:37: as a rough global indication ‘about 5% for deferred harvest and −15% [i.e. positive spillovers] for permanent set asides’). Lower leakage estimates mean more forest carbon projects can be profitable, increasing the supply of nature-based mitigation - but if the estimates in DSBE25 are wrong, overstated emissions reductions (‘hot air’) will enter both voluntary and compliance carbon markets, retarding vital short-term mitigation efforts and further eroding consumer confidence. The GTM is a valuable model, which has enlightened economists, foresters, and climate scientists for well over twenty years [4]. But it should not be used to measure leakage from individual carbon offset projects. Using the estimates in DSBE25 as adjustment factors in carbon markets creates an unacceptable risk of ‘hot air.’ In what follows, I substantiate these assertions and suggest a path forward that includes the insights of DSBE25. 1. Global model, local issues Our understanding of leakage is based on theoretical models of ideal markets, in which market boundaries (hence the relative size of the shock, and the specific firms whose supply and demand curves are relevant) and product differentiation (hence substitution) play fundamentally important roles [5]. The version of GTM used in DSBE25 [6] models a global market with one price for sawtimber and another for pulpwood; every forest type (except bioenergy plantations) produces a welfare-maximizing mix of both products. This is a world in which the timber supply deficit from a forest conservation project in the Canadian Boreal can be replaced by increased production in central Africa, or Australia. Since GTM optimizes over all time periods at once, a supply deficit today can alter harvest or investment schedules a century in the future. Marginal cost curves for broad forest ‘types’ (roughly, biome × subcontinent) drive spatial variation in market responses, but there are no trade costs (transport to market) or trade barriers (e.g. tariffs). The abstractions in GTM make sense for a model designed to capture planetary trends, [7] but the policy instruments used to incentivize forestry-based mitigation (notably carbon markets) are structured around individual projects. The median Improved Forest Management (IFM) offset project may remove the equivalent of 125 acres of forest from production every year2; the single-year shocks modelled in DSBE25 range from 0.113–53.621 million acres (median: 5.362 million acres)3. While the cumulative stock of forest carbon projects may approach DSBE’s lowest-end implementation rates in a few regions worldwide, [8] gradual implementation is not the same as a single large shock. Before carbon markets use DSBE25 to justify current leakage accounting measures (as ACR did this year) [2], the implications of GTM design choices should be carefully considered. As well as structural simplifications in GTM, the discount rate chosen in DSGE25 (a relatively aggressive though unexceptional 5%) is of central importance for interpreting and applying results. In DSBE25, leakage rates fall as the time horizon for measurement increases, because the decisions of intertemporally optimizing non-targeted producers have time to bear (time-discounted) fruit. This is good economics, but very risky policy: the results in DSBE25 may be used as ex ante adjustments to carbon credits issued today, taking it on trust that modelled supply increases will materialize as predicted 20, 50, or 80 years into the future. Using DSBE25’s leakage adjustment in forest carbon markets means allowing more emissions now in exchange for uncertain sequestration later on. The literature on overshoot, tipping points, and climate inertia is compelling [9] that this is a very bad idea. Again, the problem is not discounting itself (money-metric welfare measures should use discounting to identify economically efficient solutions, including to price impermanent forest carbon offsets [10, 11] but rather its application to physical carbon accounting. 2. Case Darkwoods To see how these methodological issues matter, consider the Verra-certified Darkwood IFM project, located in southern British Columbia, Canada. Beginning in 2008, harvest levels were reduced by about 40 000 m3 yr−1; 3 major sawmills (and various smaller facilities) in the relevant Timber Supply Area (TSA) may have responded by bidding up prices, with potential production increases capped by a regulated Annual Allowable Cut. Harvest billing data shows that TSA aggregate harvest increased by about 120 000 m3 from 2009 to 2010 and—with fluctuations due to business cycles, natural disturbances, and tariff policies—climbed steadily higher over the following decade. These increases could potentially include 100% leakage from the Darkwood project, but attributing impacts requires careful causal analysis. Since Darkwood focused on preserving old-growth cedar-hemlock forests, the very low substitutability of large-diameter cedar is clearly relevant. DSBE25’s ready-for-use estimate (table S3: ‘Canada interior’ for 2% set-asides) would assign −13% leakage (i.e. a spillover bonus) but does not account for any of these real-world factors. Instead, a global market reacts optimally on a 200 year planning horizon to replace foregone ‘wood’ by profit-maximizing ‘timber producers’ (not mill owners), anywhere in the world. Applying the DSBE25 estimate in a policy setting requires assuming that future production increases will appear as forecast. In contrast, Canada’s current federal IFM protocol for private land would apply a 71% leakage deduction, drawing on regionally-specific timber market analysis [12]. 3. Opposing evidence DSBE25’s conclusions contradict prior estimates from similar models, which commonly find market or carbon leakage rates of 70% or higher [1]. In Norway, estimates from the European Forest Institute-Global Trade Model (EFI-GTM) find 70% to >100% global leakage following harvest restrictions [13] the leakage rates by region and forest type in DSBE25 (table S3: ‘EU Nordic Plantation’) would assign 6%–18%. Like GTM, EFI-GTM is a partial equilibrium forest sector model; unlike GTM, it models 18 distinct final products and performs welfare-maximizing optimization for one period at a time. Leakage per year declines over time, as in DSBE25, but not always and often non-monotonically. In another example, leakage estimates from set-asides in the United States using the Global Forest Products Model [14] find carbon leakage of 71% (versus −3% to 4% in DSBE25: table S3). Econometric estimates of observed leakage ex poste are an important complement to modelling studies, although appropriate ‘natural experiments’ are rare. In one well-known paper, Wear and Murray [15] found 84.4% harvest leakage after federal harvest restrictions in the United States to protect Spotted Owl habitat; 26.7% was estimated to occur via increased harvest in Canada, where publicly-owned forests are regenerated by law (i.e. the long-term investment response that is central in reducing leakage in DSBE25 cannot apply). In tropical regions, where DSBE25 estimate an overall leakage ‘bonus’ of −24% to −79% (table S2: carbon leakage from Tropical Natural forests), non-substitutable timber species, rent-seeking, and inelastic local demand for fuel, among other factors, have kept leakage impacts on policy and research agendas for decades. The 2018 Kenyan moratorium on logging, for example, was immediately followed by increased harvest across the Ugandan border that probably offset all carbon gains [16]. 4. Fixing the leaky sink Good science is often a dialectic, but truth-discovery is complicated when multiple epistemologies are brought to bear. DSBE25 rely on a conventional (i.e. American) view of economic change, in which well-functioning markets relocate resources in a profit-maximizing way, given secure private tenure and complete information. As with Foster and Rosenzweig’s conclusion in the prestigious American Economic Review that demand for fibre produced more forest plantations in India, [17] DSBE25’s methods capture an important truth. But reality is often messier. Before offsetting industrial emissions using DSBE25’s results, we should ask whether they are correct. The only published back-cast validation of GTM [7] shows a laudable ability to replicate sweep-of-history changes in forestry production, but deviations between these (supra-continental) predicted and realized values are at least an order of magnitude greater than the cumulative impact of all forest carbon projects so far4. GTM’s out-of-sample predictive ability (i.e. about future market evolutions) needs testing at project scales; a pre-registered programme that compared DSBE25’s predictions against ex poste econometric estimates could fill the gap. In the meantime, we should not issue carbon credits using leakage estimates that are at odds with core elements of theoretical leakage mechanics and much prior evidence, no matter how badly we wish to scale-up carbon markets. As I have previously argued, [1] the tolerable standard of certainty in offset measurement should be set by the substituted action: this is the only way we can accurately measure progress towards climate targets and incentivize efficient mitigation. Modelling studies—like DSBE25—have a valuable role to play as part of a tiered process of truth-discovery, for example, by guiding policy interest in supply restrictions (e.g. forest carbon offsets) towards regions of the world that are worse at producing timber and better at storing forest carbon. They are not yet precise measurement tools. Instead, we should design forest carbon interventions to avoid leakage by holding production constant while simultaneously increasing forest carbon storage [19], ensuring that offsets contribute to mitigation efforts rather than mask their failure. Footnotes

Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 1. Introduction Every year, the United Nations (UN) Conference of the Parties (COP) convenes to negotiate global priorities for climate change policy. COP30, held in November 2025, introduced a first-of-its-kind ‘Declaration on Information Integrity on Climate Change’ to address how misinformation and disinformation campaigns can potentially erode public trust in climate science and democratic discourse (Ferreira 2025). More than twenty countries, excluding the United States (U.S.), will collaborate with civil society partners to implement the UN endeavor. The developments at COP30 highlight a growing global awareness of the fossil fuel industry’s alleged disinformation strategies, which have emerged as a potent tool for stalling sustainable governance (Ferreira 2025, Roberts et al 2025). In these proceedings, misinformation was generally defined as the unintentional spread of harmful or inaccurate information, whereas disinformation is the deliberate intent to mislead (Gertrudix et al 2024, p 3). The UN’s declaration not only demonstrates a strong commitment to bolstering confidence in science-based policies but also aims to protect public discourse from industry pressures (Ferreira 2025). Given this context, it is crucial to explore how the fossil fuel industry’s influence sustains society’s dependence on a carbon-intensive economy. This influence often appears in political messaging that some researchers label as climate disinformation, which can alter the public’s understanding of climate science and policy (Gertrudix et al 2024, Reyes-García et al 2025). Moreover, they argue that these messages seek to obstruct climate change legislation through a network of industry-funded advertising firms, research, think tanks, lobbying groups, and public relations organizations that amplify them (Roberts et al 2025, p 3). Through this network, industry-funded narratives can foster division and adversarial views on environmental issues, such as casting climate change science and policy as economically unsound (Gertrudix et al 2024, p 4, Sethi 2024). Studies also indicate that these narrative devices often emerge when regulations could decrease fossil fuel demand and limit industry profits. To challenge such regulations, campaigns often focus on identifying key voting constituencies at the national and subnational levels to guide opposition efforts (Ulucanlar et al 2016, Niven 2024. Plachta and Rubin 2025). However, linking alleged climate disinformation to obstruction is complex because cultural and regional policy environments shape how fossil fuel messaging is crafted and received (Barboza 2023). To better understand the scope of climate disinformation, the following sections explore California as a subnational case. The state is a world leader in addressing climate change, with both mainstream environmental and environmental justice organizations actively shaping climate policy. Shifting demographics show that support from Latino voters and lawmakers is essential to advancing environmental legislation. Yet, multinational industries and agricultural interests remain powerful in the state’s economy and governance. These elements underscore the intricate political dynamics at local, state, and transnational levels that influence California’s climate policy and initiatives (Méndez 2020; p xiii, LCA 2024). 2. California as a microcosm of misleading climate narratives The U.S. has long represented a conflicted political arena for climate action. In recent years, climate change policies have become increasingly partisan and politicized, portrayed as incongruent with economic priorities. This has led to the U.S. withdrawal from UN climate proceedings and sweeping federal rollbacks of climate-related rules, policies, and funding (Borunda et al 2025, Elbeyi et al 2025, pp 30–32). California, however, demonstrates how subnational governments can adopt effective climate policies despite national policy gridlock and intense local political conflicts (Méndez 2020). The state has consistently implemented ambitious, comprehensive climate change and environmental justice laws with stricter standards than those of the U.S. federal government (Roberts et al 2025). This leadership has become crucial amid federal regulatory backsliding. California Governor Gavin Newsom attended COP30 and the Munich Security Council to foster international partnerships, reduce carbon emissions, and enhance climate resilience. However, these climate action commitments are somewhat overshadowed by a recent decision to fast-track thousands of new oil-drilling permits through Senate Bill (S.B.) 237, a stopgap measure prompted by rising gasoline prices in the state (Gross 2025). This decision highlights the geopolitical tension between supporting global efforts to address climate change and the state’s deep-rooted dependence on a fossil-fuel economy. California ranks as the eighth-largest oil producer and the third-largest crude oil refiner in the United States. The state is also one of the world’s top gasoline consumers (EIA 2025). This reliance likely reflects the continued presence of fossil fuel companies and their trade associations in the state. Several scholars argue that trade associations serve as an important ‘command center’ within the climate obstructionist network, coordinating industry resources for lobbying, research, and advertising campaigns (Roberts et al, 2025, p. 8). These scholars further contend that trade associations often obscure their funding by establishing affiliated tax-exempt 501(c)(4) ‘social welfare’ nonprofits, allowing them to keep their donors private (Friedman 2024). This strategy can enable the industry to engage in unfettered political lobbying and public relations activities through organizations that mimic grassroots, bottom-up campaigns, a practice researchers call ‘astroturfing’ (Roberts et al, 2025, p. 42). Studies show that trade associations in the food, beverage, and tobacco sectors employ similar strategies. They often finance campaigns that resonate with minority or lower-income populations, leveraging those groups’ genuine economic or social concerns to oppose regulations that could harm industry interests (Ulucanlar et al 2016, p. 9; Tanrikulu et al, 2020, Barboza 2023). In California, the Western States Petroleum Association (WSPA) is the fossil fuel industry’s trade association. Lobbying disclosure reports show 501(c)(4) groups under WSPA’s purview spent over $40 million on advertising in the state between 2014 and 2023 (LCA 2024, table 4). Year after year, state disclosure reports show the fossil fuel industry has increased its lobbying and public relations spending in California more than in any other state in the country (Gross 2025). For example, the industry spent $10.3 million on lobbying activities in the first quarter of 2026 alone. Political experts opine that they are leveraging the Iran conflict to push back against the supposed high cost of the state’s fossil-fuel phaseout efforts (Lazo 2026). These ongoing efforts show how the industry can use the political salience of ‘affordability’ narratives (i.e. arguments that reducing carbon emissions increases utility bills, gas prices, and taxes) to advance its interests. In a 2023 Shell Corporation Climate and Energy Transition Lobbying Report, WSPA was praised for its ‘media outreach program…to increase public engagement in the state’s energy policy debate,’ and for its ability to remain relevant to ‘low-income and under-represented communities’ (Shell plc 2023, p 27). Several news articles also frame WSPA as seeking to influence Latino voters to be wary of California’s climate change laws, citing concerns about job losses and effects on their pocketbooks (Barboza 2023, Mulkern 2023, Plachta and Rubin 2025). To put this ongoing strategy into context, between 2023 and 2026, the second co-author of this letter and several of their Latino family members received multiple direct-mail pieces and social media posts from fossil fuel-related groups. These messages frequently emphasize affordability concerns and the need to prevent the adoption or implementation of climate change policies (Barboza 2023, Mulkern 2023). During the 2026 New York Climate Week, the second author also served as a panel expert at an invite-only briefing for Spanish-language broadcast and digital media on ‘Responsibilities of Emerging Technologies in Latino Communities.’ Journalists posed critical questions to the panel about climate disinformation and more effective messaging to address affordability concerns in Latino communities. 3. California Latinos and alleged climate disinformation Affordability-focused political messaging has become increasingly salient for many members of the Latino community. This population consistently experiences the highest poverty rates, accounting for nearly half of all poor Californians (Méndez and Sadhwani 2022). In response to growing affordability concerns, WSPA launched an initiative titled Levanta Tu Voz (Raise Your Voice). This narrative campaign aims to galvanize opposition among Latino voters, who they believe are adversely affected by what are being called California’s ‘costly’ climate change laws (Levanta Tu Voz 2025). Because Latinos make up a significant portion of California’s population and represent the state’s fastest-growing voter demographic, WSPA likely focuses on this group to amplify its message and legitimize its position (Venteicher 2024). The WSPA campaign primarily features Latino workers who promote slogans claiming that California’s energy transition will ‘leave Latino communities behind,’ eliminate jobs, and increase household utility bills (Levanta Tu Voz 2025). However, the Los Angeles Times reported that, in interviews with journalists, several Latinos involved in Levanta Tu Voz held nuanced views on sustainable energy, openly stating that ‘electrification is the future’ (Barboza 2023). This was followed by a Times Editorial Board (2023) piece titled: ‘Big Oil is exploiting California’s Latinos in its latest climate disinformation push.’ The board acknowledged the fossil industry’s right to free speech and lobbying. However, they underscored that while their messaging may begin with some truth about rising energy costs, the oil industry ‘offers only doubt and delay’ rather than real solutions (The Times Editorial Board 2023). Politico subsequently published an investigative news article focused on two WSPA-affiliated groups, Californians for Affordable and Reliable Energy and Californians for Energy Independence (Mulkern 2023). According to their analysis, these groups spent a combined $4.3 million in 2023 on television and Facebook ads in both English and Spanish, warning against reduced oil production and blaming state policies for higher gas and electricity prices. Consumer rights groups called the ads ‘misleading’ and labeled the organizations ‘front groups’ for the oil industry (Mulkern 2023). Academic research (Schoch et al 2022, Gertrudix et al 2024, Yang 2025) supports these claims, showing that alleged coordinated disinformation efforts can obscure industry motives through networks of business- and community-affiliated coalitions that claim to defend voters’ economic interests while protecting fossil fuel companies (Roberts et al 2025, p 68). These strategies appear across local contexts and regions, particularly focusing on shifting perspectives within communities of color. In ‘Fossil Fueled Foolery,’ a series of research reports released by the oldest and largest civil rights organization in the U.S., the National Association for the Advancement of Colored People, explores how fossil fuel companies influence public opinion and community leaders’ policy decisions. According to reports from 2019, 2021, and 2026, this approach is especially evident in African American communities in the Northeastern and Southern U.S. (Patterson 2026). These strategies also appear in California, home to long-established environmental justice groups (Méndez 2020). Latino communities often serve as important voices in these grassroots organizations, considering they are disproportionately impacted by climate change. In California and across the country, infrastructure disinvestment and exclusionary zoning leave communities of color continuously exposed to environmental health hazards from industrial and fossil fuel sites (Méndez 2020). Research has consistently shown that this historical context typically makes Latinos more supportive of and engaged with climate change policies (Roth 2020, Segura 2024). The lived experience and advocacy of Latinos in California, combined with their voting power, pose significant obstacles for the fossil fuel industry. Environmental justice groups contend that fossil fuel groups often seek to undermine Latinos’ and other communities of color’s historic support for climate change laws and policies (CEJA 2020). Artificial intelligence (AI) tools are increasingly used to challenge this support (Smith 2026). For instance, environmental advocates recently called for an investigation into an AI campaign that used residents’ identities without permission to inundate California air regulators with over 20 000 alleged fake opposition emails. The volume of comments reportedly influenced a 7–5 vote against clean air rules to phase out gas-powered appliances (Handel 2026, Zillac and Rott 2026). These efforts likely build on a long-standing strategy. A 2025 Sacramento Bee article by Plachta and Rubin noted that the industry spent millions to block building electrification, focusing on gas-powered stoves. It allegedly targeted Asian and Latino voters and restaurant owners through mail and digital campaigns, using cultural and culinary concerns to portray a diverse opposition to state initiatives. Several journalists have described these narrative framings as relying on reductive messaging that can obscure the complex, layered economic and environmental health conditions Latinos face (Roth 2020, Barboza 2023, Mulkern 2023, Plachta and Rubin 2025). Additionally, climate disinformation campaign messages become harder to counter when mainstream environmental groups, such as the Natural Resources Defense Council and the Environmental Defense Fund, have not substantively addressed climate change as a socioeconomic and public health issue. Scholars view this as a missed opportunity to link climate change impacts to ‘kitchen-table’ economic and health issues that matter to Latino communities (Méndez and Sadhwani 2022). Within California’s legislative halls, there is nuanced pushback to climate disinformation from several Democratic Latino legislators who are confronting the local socio-economic realities of environmental laws. Research shows these members often come from politically moderate rural and suburban regions in the San Joaquin Valley and Orange County. In many of these competitive districts, Democratic voter registration led Republican registration by only a few percentage points. This means these legislators must strike a delicate balance between environmental stewardship and economic development to remain in office (Méndez 2020). Studies further show that Latino voters in these communities often respond to industry arguments about the cost of environmental regulation, such as increased energy costs for residents or the loss of blue-collar jobs in their regions. This reality has pushed several Latino legislators to reframe climate change legislation as a public health issue and a means of local job creation, ultimately leading to the adoption of multiple statewide climate initiatives. In essence, to counter disinformation efforts, Latino legislators have often balanced fiscal and environmental justice concerns. They highlight the natural and material consequences of climate change as a core message, alongside potential public health and job-creation opportunities of climate change laws (Méndez 2020, pp 62–64). 4. Future policy and research outlook The economic and public health resilience of low- and middle-income communities is intrinsically tied to the climate crisis, as worsening climatic effects exacerbate historic injustices along racial and class lines. To confront the false dichotomy between economic and environmental concerns, policymakers and mainstream environmental groups should communicate beyond abstract, globally focused climate change policy. By not tethering climate change concerns to lived, local realities, campaigns like WSPA’S Levanta Tu Voz can more readily leverage genuine fears about job loss, household and energy affordability, and familial livelihoods within Latino, Black, Indigenous, and working-class communities (Meisei 2025). Ensuring a culturally relevant and human-centered approach to climate change policy requires the active involvement of community-based environmental justice organizations that have, for decades, articulated the importance of centering equity and affordability in climate change laws (Meisei 2025). However, research shows these groups are often excluded from sustainable governance dialogues or, when included, are tokenized in their participation and lack substantial decision-making influence (Méndez 2020). Forging synergistic, cross-sectoral climate coalitions between grassroots and mainstream environmental actors could pose a critical challenge to industry-funded networks. Studies underscore that climate disinformation networks are formidable largely because they coordinate powerful actors across spheres of influence. Their depth, reach, and funding strengthen their rapid growth (Roberts et al 2025, p 145). Therefore, additional research is needed to examine the long-term stability of climate disinformation campaigns globally, in contentious regions such as California, and beyond ‘WEIRD’ countries: Western, Educated, Industrialized, Rich, and Democratic (Roberts et al 2025, p 85; 203). Longitudinal comparisons of disinformation campaigns can also identify variables and strategies across regional, policy, and cultural contexts (Gertrudix et al 2024, Elbeyi et al 2025, Yang 2025). This research can help civil society and policymakers address the growth and evolution of climate disinformation more effectively (Niven 2024). While campaigns like WSPA’s expand, it is equally important to highlight community-driven innovations that counter these strategies. Across the country, groups are strengthening media literacy, conducting multilingual fact-checking and community reporting, and promoting scientific, place-based environmental and political education (LCA 2024, Niven 2024, Bisht et al 2025, Elbeyi et al 2025, Roberts et al 2025). As reflected in the UN’s Initiative on Climate Information Integrity, international venues can effectively champion on-the-ground programs to address climate disinformation (Ferreira 2025). This is also evident in GreenLatinos, a U.S.-Latino-led environmental justice nonprofit. Their ‘Climate Loteria’ campaign uses culture, humor, and multilingual dialogue to educate Latinos about disinformation (Meisei 2025). Similarly, Climate Power En Acción (2025), a Latino environmental group, monitors Spanish media and social networks to fact-check climate-denial messages. Alongside Sachamama, they also launched Latido Climático (Climate Heartbeat), a campaign featuring local events to combat disinformation and show climate action’s economic and health benefits. In 2026, they held over 1500 events. They seek to reach millions of Latinos nationwide. These examples show that information integrity initiatives can succeed when environmental institutions collaborate with the grassroots. Nurturing these ‘seed’ initiatives can build momentum by leveraging community resources, such as social capital and skills development, to create transformative pathways, even amid social, political, and environmental challenges (Bennett et al 2016). To accomplish this, we need to understand disinformation networks, expand the mainstream environmental movement, and ensure policymakers prioritize the needs of low-income residents and communities of color in climate change strategies. COP30 emphasized that maintaining information integrity is essential to safeguarding multilateral progress on climate action. Evidently, growing support for science-based climate change policies relies on collective trust in fundamental resources: information sharing and relationship building. The author(s) declared the following regarding funding or potential conflicts of interest with respect to the research, authorship, and/or publication of this article: This research project was supported by funding from the Andrew Carnegie Foundation Fellowship and the UCLA Latino Policy and Politics Institute. In addition, the second author serves as a gubernatorial appointee to the California Regional Water Quality Control Board (Region 4). The board engages with regulated industries, local governments, and community residents regarding several issues identified in this letter. Further, Climate Power En Acción and The Climate Group, both not-for-profit environmental organizations, covered the second author’s travel expenses for the 2026 New York Climate Week event. Data availability statement No new data were created or analysed in this study.

Loader page.

Loader page.

To ensure we keep this website safe, please can you confirm you are a human by ticking the box below. If you are unable to complete the above request please contact us using the below link, providing a screenshot of your experience. https://ioppublishing.org/contacts/

Published 5 November 2026 • © 2026 The Author(s). Published by IOP Publishing Ltd Environmental Research Letters, Volume 21, Number 21Citation V Cologna et al 2026 Environ. Res. Lett. 21 219501DOI 10.1088/1748-9326/aea350 Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 1. Short statement The market research company that collected the survey data for this study made consequential mistakes when recruiting respondents, such that some participants were sampled twice. Specifically, 44 participants who had filled out the survey twice pre-vote had different IDs in our dataset but actually reflected the same people. Post-vote, we identified 57 participants who had completed the survey at least twice with some of these participants getting access to two separate survey links and viewing both conditions. Correcting these mistakes slightly changed the results of some of our analyses. The values in the original manuscript should therefore not be taken at face value; readers should instead consult the tables in this correction. Our substantive conclusions are largely unaffected. We continue to find no evidence that advocacy backfired among right-leaning respondents, no effect of advocacy on the voting intentions or self-reported voting behavior, a significant interaction between treatment and political orientation on trust pre-vote, and a significant positive effect of the treatment on trust post-vote. However, the evidence for a positive main effect of the treatment on trust in the pre-vote survey is now weaker and model-dependent: It becomes no longer significant in the model without socio-demographic covariates (p = .071) and only marginally significant in the model with covariates (p = .049). Thus, this pre-vote effect should be interpreted with caution. Finally, the coefficients in our original tables were labeled as standardized, but only the income variable was standardized. The tables now correctly indicate unstandardized coefficients (b). 2. Why do we suggest this correction? The market research company that collected the survey data underlying this study made a consequential mistake when recruiting the respondents: A few participants were sampled twice. Correcting this mistake changed the results of some analyses slightly, however, critically, the main results remained largely unaffected. In the following, we explain in detail what happened and how we corrected the mistake. 3. How did we collect data for this study? Data was collected by a market research company with a pool of Swiss panelists. For the first survey (pre-vote), we asked the market research company to resample participants from the trust in science and science-related populism (TISP) study, as well as collecting data from additional participants (see pre-registration). Pre-vote, we created one survey link—which was sent to the market research company—and participants were randomly assigned to either a control or a treatment group. Post-vote, we created two separate surveys: one for the control group and one for the treatment group. We sent the market research company the two survey links—one for the control group and one for the treatment group—with a list of the IDs that had to be invited to each of the surveys. This would ensure that participants who were in the control group pre-vote would be invited to participate in the control group post-vote, and vice versa. 4. What happened? The market research company opened two projects on their end: one to resample TISP participants and one to sample participants from a new pool of panelists. In doing so, the project manager at the company erroneously allowed panelists resampled from TISP to also participate in the second project, thus allowing some participants to participate in the study twice. Since these were separate projects, panelists who participated twice were assigned two different IDs in our survey. On our end, it was therefore impossible to see that the same participants had participated in the study twice albeit with different IDs. Only the market research company could have seen this, because their panelists have unique identifiers on their end that, for data privacy reasons, are not accessible to their clients (i.e. in this case us). As 44 participants were allowed to participate twice in the pre-vote survey, some were assigned to the control group twice, and some to the treatment group twice and in many cases, they were assigned to the control and the treatment group. Since these participants had completed both conditions, their IDs were added to both the control group and the treatment group lists that we sent to the market research company to resample participants post-vote. Therefore, these participants received two invitations in the post-vote survey: one to participate in the control group and one to participate in the treatment group. Some of these participants completed both surveys post-vote. An additional problem we observed, but for which the company has not been able to provide an explanation because the project manager responsible for this project has left the company, is that some participants who had only completed one condition pre-vote were able to access both surveys post-vote (control and treatment), i.e. got access to both survey links. 5. How did we notice this? When running further analyses for another paper using the same dataset, we noticed that some participants were not correctly reassigned to the same condition post-vote. For example, some participants were in the control condition pre-vote and in the treatment condition post-vote. We contacted the market research company to find out how this could have happened. While inspecting this, they noticed that the same participants had completed the pre-vote study twice with different IDs. However, the company could not give an explanation as to how other participants gained access to both survey links post-vote. 6. What did we do to correct the dataset? Pre-vote. We asked the market research company to inform us which IDs were linked to the same participants so that we could inspect duplicate responses from the same participants (we uploaded the raw dataset with this information on OSF). Overall, 44 unique participants filled out the survey twice (with different IDs on our end). For example, the same participant could have had ID = 12 345 when first completing the survey and ID = 67 891 when completing the survey a second time. We created new unique IDs by linking the two IDs and sorting them so that the order of survey completion did not matter (e.g. 12345_67891). We retained the first complete response and deleted the second response. This decreased our sample from n = 1622 to n = 1578. The remaining analyses pre-vote remained unchanged (see code with step-by-step description on OSF). Post-vote. We collected n = 940 complete responses. As in the pre-vote survey, we created unique IDs based on the new information provided by the market research company. In total, we identified 57 duplicate responses, of which 12 were from participants who completed both conditions pre-vote and one participant completed the survey three times, leading to 58 excluded responses. The remaining participants had somehow gained access to both survey links. (Note: In the original publication we removed 48 duplicate responses, namely, those who had already appeared as duplicates on our end). First, we deleted duplicate complete responses by retaining the first post-vote response, as done pre-vote (n = 58 responses removed). Second, we also deleted responses of participants who had been assigned to a different condition pre- and post-vote (n = 49 responses removed). For example, if participant 12345_67891 was in the control group pre-vote and in the treatment group post-vote. Lastly, we removed participants who had completed both conditions pre-vote and had therefore been exposed to both the control and the treatment materials (n = 19 responses removed). Of these n = 19 responses, n = 11 had already been removed because they were assigned to a different condition pre- and post-vote and n = 2 had already been removed during the first step of deleting duplicate responses. Effectively, we therefore removed n = 6 participants in this last step. Together, these steps decreased our final post-vote sample from n = 891 before correction to n = 827 (940 − 58 − 49 − 6 = 827) after correction. All of these steps are detailed in the code published on OSF. Additionally, we note that our tables previously indicated standardized coefficients, but we relabeled them to unstandardized coefficients, as only the income variable was standardized. 7. How did this affect our results? Our substantive conclusions largely remained unaffected by these changes, but the evidence for one result weakened. Pre-vote, the effect of the treatment (vs control) on trust in scientists changed from b = 0.07, p = .047 to b = 0.06, p = .071 in the model without socio-demographic covariates, and from b = 0.08, p = .035 to b = 0.07, p = .049 in the model with covariates. The pre-vote main effect of the treatment is thus no longer significant in the model without covariates and only marginally significant at the conventional p < .05 threshold in the model with covariates. Hypothesis H2a, which we described as partially supported in the original manuscript (the t-test was non-significant), therefore now has weaker partial support. Post-vote, the effect of the treatment on trust in scientists changed from b = 0.12, p = .018 to b = 0.13, p = .014. The interaction effect of the treatment (vs control) and political orientation on trust pre-vote remained significant, changing from b = − 0.10, p = .008 to b = − 0.09, p = .017 in the model with sociodemographic covariates. This interaction term remained non-significant post-vote, changing from b = − 0.03, p = .512 to b = − 0.05, p = .332. More generally, we note that the treatment effects on trust are small. Unstandardized coefficients of 0.06–0.13 on a 5-point scale, corresponding to standardized differences of ca. 0.1–0.2, at or below the smallest effect size (d = 0.20) the study was powered to detect. The fact that effects of this size move across the p = .05 threshold when duplicate participants are removed reflects their fragility. Readers should therefore give more weight to the effect sizes and confidence intervals than to whether individual models fall marginally above or below the significance threshold. For transparency, our OSF folder includes the corrected datasets and code, as well as the original datasets and code. 8. Corrected tables and figure in main manuscript Corrected tables 1–5 as well as corrected figure 1 can be found below. Table 1. Blockwise linear regression on trust in scientists (pre-vote). Trust in scientists (Intercept) 3.49 3.45–3.54 143.69 <.001 3.41 3.28–3.53 52.60 <.001 Advocacy letter treatment 0.06 −0.01–0.13 1.81 .071 0.07 0.00–0.14 1.97 .049 Political orientation (right) −0.06 −0.11—−0.01 −2.39 .017 −0.06 −0.11—−0.01 −2.29 .022 Treatment * Political orientation (right) −0.08 −0.15—−0.01 −2.20 .028 −0.09 −0.16—−0.02 −2.38 .017 Male 0.06 −0.02–0.13 1.55 .121 Language region: Italian −0.05 −0.18–0.08 −0.79 .430 Language region: French 0.03 −0.05–0.11 0.83 .407 Residence: urban 0.17 0.09–0.24 4.45 <.001 Age (in years) −0.00 −0.00–0.00 −0.57 .570 Income (in CHF) 0.03 −0.01–0.08 1.63 .103 Observations 1353 1207 R2/R2 adjusted 0.027/0.025 0.054/0.047 Note: Language regions are compared to German. Residence: 1 = Urban, 0 = Rural. Gender: 1 = Male, 0 = Female, other responses were coded as missing. Political orientation = 1 (strongly left-leaning), 5 (strongly right-leaning). Baseline is placebo letter treatment. Pre-vote survey wave. Political orientation was centered and income standardized. Values in bold are statistically significant at p < .05. Table 2. Linear regression predicting trust in scientists post-voting. Trust in scientists post-voting (Intercept) 3.36 3.16–3.55 34.15 <.001 Advocacy letter treatment 0.13 0.03–0.23 2.47 .014 Political orientation (right) −0.09 −0.16—−0.02 −2.47 .014 Gender: male 0.12 0.02–0.23 2.30 .022 Language region: Italian 0.04 −0.14–0.22 0.45 .651 Language region: French 0.10 −0.02–0.22 1.71 .088 Residence: urban 0.22 0.12–0.33 4.18 <.001 Age (in years) −0.00 −0.01–0.00 −1.74 .083 Income (in CHF) 0.02 −0.03–0.08 0.85 .393 Treatment * Political orientation (right) −0.05 −0.16–0.05 −0.97 .332 Observations 650 R2/R2 adjusted 0.083/0.071 Note: Language regions are compared to German. Residence: 1 = Urban, 0 = Rural. We included the non-preregistered interaction term treatment * political orientation to be able to compare results with the pre-vote survey. Political orientation was centered and income standardized. Values in bold are statistically significant at p < .05. Table 3. Blockwise linear regression on normative perceptions (pre-vote). Normative perceptions of scientists in society and policymaking (Intercept) 3.76 3.70–3.82 123.37 <.001 3.82 3.66–3.98 47.32 <.001 Advocacy letter treatment 0.06 −0.02–0.15 1.49 .137 0.05 −0.04–0.14 1.18 .237 Political orientation (right) −0.13 −0.19—−0.07 −4.19 <.001 −0.14 −0.20—−0.08 −4.26 <.001 Treatment * Political orientation (right) −0.10 −0.19—−0.01 −2.22 .026 −0.08 −0.18–0.01 −1.83 .067 Male −0.00 −0.09–0.09 −0.01 .991 Language region: Italian 0.11 −0.05–0.27 1.34 .181 Language region: French −0.05 −0.14–0.05 −0.89 .374 Residence: urban 0.17 0.08–0.27 3.78 <.001 Age (in years) −0.00 −0.01–0.00 −1.83 .067 Income (in CHF) 0.02 −0.04–0.07 0.58 .565 Observations 1353 1207 R2/R2 adjusted 0.050/0.048 0.072/0.065 Note: Language regions are compared to German. Residence: 1 = Urban, 0 = Rural. Gender: 1 = Male, 0 = Female, other responses were coded as missing. Political orientation = 1 (strongly left-leaning), 5 (strongly right-leaning). Baseline is placebo letter treatment. Pre-vote survey wave. Political orientation was centered and income standardized. Values in bold are statistically significant at p < .05. Table 4. Logistic regression predicting voting intentions pre-vote. Voting intention (yes vs no) (Intercept) 0.01 0.00–0.04 −4.86 <.001 Advocacy letter treatment 0.92 0.57–1.49 −0.33 .739 Trust in scientists 5.02 3.18–8.18 6.70 <.001 Political orientation (right) 0.77 0.58–1.03 −1.76 .078 Political party: SVP 0.21 0.11–0.40 −4.79 <.001 Gender: male 0.83 0.49–1.42 −0.69 .493 Language region: Italian 0.82 0.32–2.21 −0.41 .683 Language region: French 0.63 0.35–1.13 −1.55 .121 Residence: urban 1.84 1.11–3.07 2.36 .018 Income (in CHF) 1.00 0.80–1.30 −0.00 .999 Age (in years) 0.97 0.96–0.99 −3.36 .001 Climate change concern 2.26 1.75–2.97 6.07 <.001 Father of girl: Yes 1.90 0.82–4.66 1.45 .146 Observations 595 R2 Tjur 0.467 Note: Voting intentions: 1 = yes, 0 = no. Model excludes participants who selected the response options ‘I would abstain’ (n = 141) and ‘I do not know’ (n = 198). Language regions are compared to German. Residence: 1 = Urban, 0 = Rural. Income was standardized. Values in bold are statistically significant at p < .05. Table 5. Logistic regression predicting self-reported voting behavior post-vote. Self-reported voting behavior (yes vs no) (Intercept) 0.00 0.00–0.04 −4.60 <.001 Advocacy letter treatment 0.64 0.37–1.11 −1.57 .116 Trust in scientists 5.87 3.67–9.82 7.06 <.001 Political orientation (right) 0.57 0.41–0.78 −3.45 <.001 Political party: SVP 0.62 0.29–1.29 −1.29 .196 Gender: male 0.84 0.46–1.50 −0.58 .559 Language region: Italian 4.66 1.40–18.42 2.35 .019 Language region: French 1.52 0.81–2.92 1.28 .200 Residence: urban 0.79 0.45–1.38 −0.82 .412 Income (in CHF) 1.00 0.80–1.29 0.01 .996 Age (in years) 0.98 0.97–1.00 −1.93 .054 Climate change concern 2.35 1.76–3.19 5.67 <.001 Observations 428 Note: Self-reported voting behavior: 1 = yes, 0 = no. Model excludes participants who did not vote (n = 188) and selected the response options ‘Prefer not to say’ (n = 31). Language regions are compared to German. Residence: 1 = Urban, 0 = Rural. Income was standardized. Values in bold are statistically significant at p < .05. 9. Further corrections in the main manuscript The statement in the abstract that ‘scientists’ advocacy was associated with greater public trust, particularly among left-leaning individuals’ remains supported by the corrected analyses. However, we note that the pre-vote association is small and only marginally significant when controlling for socio-demographic variables. The association among left-leaning individuals (the treatment x political orientation interaction) and the post-vote association remain significant. Before correction: More than half (55.51%) of participants in the treatment condition believed the advocating scientists were objective (14.37% believed they were not objective; 30.11% were neutral). After correction: More than half (55.64%) of participants in the treatment condition believed the advocating scientists were objective (14.32% believed they were not objective; 30.04% were neutral). Pre-vote difference in trust in scientists between the treatment and control group before correction (Mtreatment = 3.51, SD = 0.65; Mcontrol = 3.46, SD = 0.64; t(1618) = − 1.580, p = .114) and after correction (Mtreatment = 3.51, SD = 0.65; Mcontrol = 3.47, SD = 0.63; t(1575) = − 1.425, p = .154). Post-vote difference in trust in scientists between the treatment and the control group before correction (Mtreatment = 3.49, SD = 0.68; Mcontrol = 3.42, SD = 0.68; t(857) = − 1.577, p = .115) and after correction (Mtreatment = 3.50, SD = 0.69; Mcontrol = 3.42, SD = 0.69; t(805) = − 1.654, p = .099). Exploratory paired t-tests showed no significant differences in trust in scientists pre- and post-vote before the correction within the control (tpaired(488) = 1.426, p = .154) and treatment (tpaired(390) = 1.952, p = .052) groups and after the correction within the control group (tpaired(446) = 1.333, p = .183) and treatment (tpaired(379) = 1.930, p = .054) groups. Pre-vote differences in normative perceptions between the treatment and control group before correction (Mtreatment = 3.79, SD = 0.84; Mcontrol = 3.74, SD = 0.80; t(1615) = − 1.280, p = .201) and after correction (Mtreatment = 3.79, SD = 0.84; (Mcontrol = 3.75, SD = 0.79; t(1571) = − 0.964, p = .335). Post-vote differences in normative perceptions between the treatment and control group before correction (Mtreatment= 3.80, SD = 0.85; Mcontrol = 3.62, SD = 0.87; t(863) = − 3.161, p = .002) and after correction (Mtreatment= 3.82, SD = 0.85; Mcontrol = 3.64, SD = 0.87; t(810) = − 2.971, p = .003). Paired t-test for normative perceptions between control groups pre and post before correction (tpaired(488) = 2.984, p = .003) and after correction (tpaired(446) = 2.588, p = .01). In the discussion section, ‘right-leaning’ was corrected to ‘left-leaning’ in the sentence below. This corrects a reporting error in the original text rather than a change resulting from the corrected data. The negative coefficient for political orientation (right) in table 3 of the original manuscript already indicated that more right-leaning participants held weaker, not stronger, normative perceptions, so the original sentence contradicted the reported model. The corrected sentence reads: ‘Furthermore, residents of urban (vs rural) regions as well as people with more right-leaning political views tended to have stronger normative perceptions regarding scientists’ involvement in society and policymaking (Cologna et al 2024).’ Before correction: About half (53.3%) of our participants indicated that they planned to vote in favor of the CPL in the pre-vote survey (25.2% intended to vote against, 8.8% to abstain, and 12.8% did not know). After correction: 53.6% planned to vote in favor (24.9% against, 8.9% abstain, 12.6% did not know). Before correction: 61.7% reported that they actually voted in favor of the law, which remained unchanged after correction.ants indicated that they planne Before correction: the final pre-vote sample was n = 1622 (n = 815 control, n = 807 treatment), 49.6% female, mean age 44. After correction: n = 1578 (n = 789 control, n = 789 treatment), 49.9% female, mean age 44. Before correction: the final post-vote sample was n = 891 (n = 489 control, n = 402 treatment), 46% female, mean age 47, resampling rate 59.25%. After correction: n = 827 (n = 447 control, n = 380 treatment), 45.9% female, mean age 48, resampling rate 52.41%. V.C. acknowledges support from the Swiss National Science Foundation Postdoc Mobility fellowship (P500PS_202935) and the Harvard University Faculty Development Fund. Conflict of interest R.K. and M.S.S. are signatories of the public statement in support of the Climate Protection Law.

Loader page.

Hackers targeted 61 public GitHub repositories in a coordinated command injection campaign designed to steal data from automated development systems. Radware researchers identified 83 malicious issues, pull requests, and comments posted on September 1, 2026, with evidence that injected commands executed inside two GitHub Actions workflows. The findings show how routine project discussions can become entry points into software build systems. According to Radware’s investigation, 77 malicious items appeared within about 43 minutes. Six more followed in a second wave lasting roughly two minutes. Targets included Google LangExtract, Trivy, Brave Browser, MLflow, ToolJet, and PX4-Autopilot. Their inclusion does not mean every project was breached. The attack chain (source: Radware ) The campaign exploited workflows that placed user-controlled text directly into shell scripts. GitHub Actions can automatically respond when someone opens an issue, submits a pull request, or posts a comment. These tasks may check titles, assign labels, or send notifications. Hackers Target 61 GitHub Repositories Attackers placed Bash command substitution expressions, written as $(), inside that content. When a vulnerable workflow inserted the text into executable shell code, Bash treated the embedded expression as a command rather than ordinary text. Wrapping the inserted title in double quotes did not prevent execution. The payload ran env to collect environment variables, encoded the output with Base64, removed newline characters, and used curl to attempt an HTTP POST request. PX4/PX4-Autopilot — Pull Request #28488 (source : Radware ) Every verified payload pointed to 54.205.16[.]142 on port 8443, with a separate collection identifier for each attempt. Despite the port number, the connection used HTTP rather than HTTPS. The risk depended on what each job could access. Environment variables could contain service tokens, deployment credentials, or internal settings. GitHub Actions secrets are not automatically available to every workflow, so execution alone does not establish that sensitive credentials were stolen.  Snouzy/workout-cool Issue #251, showing the command-injection payload in the Issue title (source : Radware ) In PX4-Autopilot, a pull request posing as a documentation correction carried the payload in its title. A title-checking workflow inserted that title into a Bash command invoking Python. Logs showed a command-substitution warning and returned content beginning with GIF89a, replacing the malicious expression. In Snouzy/workout-cool, an issue notification workflow inserted the attacker’s title directly into a Bash variable assignment. A warning tied to that line confirmed command substitution. A later Discord request failed because its body contained invalid JSON, although that failure did not prove successful data theft. Radware did not confirm stolen secrets, repository write access, source code changes, or compromised releases. Researchers also found signs that some participating accounts may have been hijacked, including one owner publicly denying opening a malicious issue. The findings complement earlier reporting on GhostAction credential theft and the tj-actions supply chain attack . Those incidents used different routes but also put CI/CD secrets at risk.  Account-owner comments denying authorship of the Issue and reporting subsequent account-protection actions (source : Radware) Maintainers should pass untrusted titles through environment variables instead of inserting them into shell source, avoid eval, and limit workflow permissions. Teams finding execution evidence should review available secrets, rotate potentially exposed credentials, inspect audit logs, and investigate unexpected outbound traffic. Keep notification jobs separate from privileged release workflows to reduce the damage an injected command could cause. Give your SOC the alert context to stops incidents quickly. Integrate Threat Intel from 16K SOCs . The post Hackers Target 61 GitHub Repositories With Command Injection Attacks to Steal CI/CD Secrets appeared first on Cyber Security News .

Is Radware Cloud WAF down right now? Check the latest outage reports and share your experience. Get real-time alerts when Radware Cloud WAF is down.

Loader page.

Stock Titan provides an ultra-fast stock market news feed and multiple tools for traders and investors.

Heleen A de Wit and Jesper Bak Published 30 October 2026 • © 2026 The Author(s). Published by IOP Publishing Ltd Environmental Research Letters, Volume 21, Number 21Citation Filip Moldan et al 2026 Environ. Res. Lett. 21 211001DOI 10.1088/1748-9326/aeb70e Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 1. Introduction Forests are at the centre of two major environmental policy agendas. They are expected to provide durable carbon (C) sinks that help countries meet climate targets (e.g. [1]). At the same time, forests are exposed to, and partly shaped by, reactive nitrogen (N) inputs that contribute to eutrophication, biodiversity loss, soil acidification and nitrous oxide emissions [2–5]. Although coupled carbon and nitrogen cycling is a fundamental concept in ecosystem science, climate policy and nitrogen policy are often treated as separate domains. Carbon stock changes in forests are reported under the United Nations framework convention on climate change (UNFCCC), whereas reactive nitrogen flows are addressed through air pollution policy, including the Convention on long-range transboundary air pollution (CLRTAP) and its Task Force on Reactive Nitrogen. In forest ecosystems, considering carbon and nitrogen together is a logical consequence of their biogeochemical coupling [6–8]. Changes in forest carbon and nitrogen stocks fundamentally reflect changes in organic matter pools, including living biomass, litter, dead wood and soil organic matter, of which both carbon and nitrogen are essential constituents. If forests are accumulating carbon, they must either receive new nitrogen from outside the system or redistribute and recycle nitrogen already present within these organic matter pools more efficiently. In practice, more efficient internal recycling means that organic matter with high C/N ratios, such as woody biomass, accumulates at the expense of nitrogen-rich organic matter elsewhere in the system, particularly in soils. Carbon accumulation in woody biomass may therefore temporarily occur without a corresponding increase in total ecosystem nitrogen stocks through redistribution of nitrogen among organic matter pools. Either way, over sufficiently long timescales, estimates of ecosystem carbon and nitrogen dynamics should remain broadly consistent, provided that they cover compatible system boundaries and that all relevant inputs and outputs are included and quantified consistently. Agreement between estimates derived from different accounting frameworks would increase confidence in both, whereas persistent discrepancies may indicate incomplete accounting of boundary fluxes, methodological weaknesses or unresolved ecosystem processes. Together, Sweden, Finland and Norway contain more than one-third of the forest area of the EU-27, United Kingdom, Norway and Switzerland, making the region important for European forest carbon accounting. We compared forest N dynamics indicated by: (i) national nitrogen budgets (NNB) based on quantified inputs and outputs, and (ii) the N accumulation stoichiometrically implied by reported C-stock changes using compartment-specific C/N ratios. The nitrogen budgets were close to balance, with small residuals between the quantified inputs and outputs. In contrast, reported C-stock changes combined with compartment-specific C/N ratios implied substantial nitrogen accumulation. These two perspectives can temporarily be reconciled if nitrogen is effectively redistributed from organic matter with relatively low C/N ratios to organic matter with higher C/N ratios. Over longer timescales, however, continued redistribution of nitrogen towards organic matter with higher C/N ratios could contribute to nutrient imbalances and reduce the persistence of the forest carbon sink. The key issue is not to evaluate either accounting framework in isolation, but to understand what the discrepancy reveals about the processes sustaining forest carbon accumulation, because different explanations imply different trajectories for future carbon sequestration. 2. A nitrogen accounting discrepancy The comparison rests on two nitrogen accounting perspectives applied to forests in the three Nordic countries. The first is a NNB approach following the CLRTAP Task Force on Reactive Nitrogen methodology for the forest and semi-natural vegetation pool [9]. For the forest sub-pool, the main inflows are atmospheric deposition, biological nitrogen fixation and, where relevant, forest fertilization (figure S1). The main outflows are harvest removal, runoff to surface waters and gaseous losses through denitrification. The NNB residual is used here as an estimate of net ecosystem N stock change, recognizing that omitted or misestimated boundary flows add uncertainty. Internal cycling of N within the forest is not included, as it does not cross the system boundary. The second perspective starts from forest C stock changes reported to the UNFCCC and calculates the N accumulation they would stoichiometrically imply under fixed compartment-specific C/N ratios (table S1). The resulting C-stock-change (CSC) estimate is therefore not a direct observation of N-stock change but quantifies the N accumulation required under these stoichiometric assumptions. The system boundaries and spatial and temporal bases of the two approaches, and their implications for the comparison, are summarized in table S2. In principle, and over sufficiently long timescales, the N requirement implied by the CSC approach should be broadly compatible with the corresponding NNB residual. Instead, the CSC-implied N requirement substantially exceeds the NNB residual in all three countries (figure 1). For Sweden, the difference between the two approaches is 8.5 kg N ha−1 yr−1; the respective differences are 3.8 kg N ha−1 yr−1 in Norway and 3.1 kg N ha−1 yr−1 in Finland. These discrepancies are of the same order of magnitude as, or larger than, the total annual external N supply from atmospheric deposition, biological fixation and forest fertilization. 3. Reconciling the two approaches Several explanations can be considered. A first possibility is that some external N inputs are underestimated. The most obvious candidate is biological N fixation, which varies with stand development, bryophyte abundance, disturbance history and N deposition [10–12]. A synthesis of 18 boreal wildfire chronosequences [13] found that known N deposition and moss-associated N fixation did not explain observed post-fire N accumulation, pointing to poorly quantified fixation pathways and geological N as possible additional sources. However, these sources were not shown to close the balance, and the post-fire systems differ from the national managed forests considered here. Underestimated inputs may therefore contribute to the discrepancy, but no omitted source of sufficient magnitude to close it, particularly in Sweden, has yet been demonstrated. A second possibility is that atmospheric N deposition is underestimated. This also seems unlikely as a full explanation. National deposition estimates in Europe are based on well-developed monitoring and modelling systems and agree well between measured and modelled values at large scales [14]. Although local uncertainties remain, a systematic underestimation sufficient to close the gap in all three countries would be surprising. A third possibility is that N losses are misestimated. Denitrification is particularly uncertain and is often described as one of the least well-constrained pathways in the N cycle [15]. We have used a conservative estimate of denitrification loss, at or below the lower end of values suggested in the NNB guidance [9]. Similar considerations apply to leaching losses, which are also spatially variable and methodologically uncertain; higher actual leaching would exacerbate the mismatch, whereas overestimation could partly reduce it. Nitrogen removal through biomass harvest is another major loss pathway. These estimates are considered robust, but uncertainties remain, for example in biomass composition and N content. While overestimation of harvest losses could contribute to narrowing the gap, it is unlikely to explain the full magnitude of the discrepancy. Uncertainties are also present in the estimation of C stock changes used to infer N accumulation. Changes in forest biomass are typically based on repeated inventories and are well constrained. Estimates of soil C stock changes are more uncertain. While some countries, such as Sweden, include repeated soil sampling, these measurements remain challenging to interpret given large spatial variability and the small magnitude of annual changes relative to total soil C stocks. In many cases, soil estimates rely partly on modelling and assumptions about soil depth and turnover. As a result, calculated C stock changes are sensitive to methodological choices. The conversion to implied N accumulation is further affected by variability in compartment-specific C/N ratios associated with climate and tree species; long-term N fertilization can also alter humus-layer C/N ratios [16]. A Monte Carlo sensitivity analysis incorporating uncertainty in both C-stock changes and compartment-specific C/N ratios showed that the 95% intervals for CSC-implied N accumulation remained above the corresponding NNB residuals in all three countries (Supplementary Material). Other methodological differences in temporal averaging, forest-area definitions, compartment coverage and soil treatment may widen or narrow the discrepancy but have not been demonstrated to account for its full magnitude, particularly in Sweden (table S2). One testable hypothesis is that the mismatch reflects internal redistribution of N rather than missing external inputs or overestimated outputs. Boreal forest soils contain organic N pools far exceeding annual inputs (figure 2). If part of this soil N is mobilized and transferred to organic matter with a higher C/N ratio, forests could continue to accumulate C without equivalent new N inputs. This would not remove the N constraint but shift it in time, allowing forests to draw on a pre-existing stock of soil N. This interpretation has an observable consequence. If soils supply N while retaining or gaining C, soil organic matter should gradually become more N-poor and soil C/N ratios should increase. Assuming N redistribution to support the C gain, calculated annual increases in soil C/N ratios are about 0.13–0.14 in Sweden and Finland, and about 0.02 in Norway (table S3). The Norwegian estimate is small, but the Swedish and Finnish values are large enough to be testable in long-term monitoring. Existing evidence remains inconclusive: long-term observations in southern Finland found decreasing total N concentrations and increasing C/N ratios in the organic layer but no general decline in mineral-soil total N [17], while a post-fire chronosequence synthesis found increasing upper mineral-soil N, implying that any transfer from deeper soil would have to be large [13]. Furthermore, mining organic N from deeper soils requires mineralization of soil organic matter (i.e. CO2 respiration from lower horizons) leading to C loss in subsoils that may be less well monitored in C accounting. 4. What does this mean for interpreting forest carbon sinks? Forest C sinks are often discussed and reported primarily in relation to climate, management and disturbance, while the nitrogen requirements associated with sustained carbon accumulation are not routinely assessed within greenhouse-gas inventory frameworks. Stoichiometric reasoning suggests otherwise. Nitrogen availability affects biomass production, litter quality, decomposition and soil organic matter formation, particularly in high-latitude forests [6, 7, 18]. If current C accumulation depends partly on redistribution of N from legacy soil pools, the sink may be less persistent than annual C stock changes alone would suggest. High-latitude regions with a modest legacy of N deposition may be among the first to experience N constraints on C sequestration, despite rising atmospheric CO2 [19]. The discrepancy does not by itself imply that reported forest C accumulation is overestimated. Biomass changes derived from repeated inventories are generally robust, whereas uncertainty is larger for dead organic matter and soils, where changes are smaller relative to spatial variability and values are often model-based [20]. The key point is that C accumulation does not by itself indicate whether N supply is sustainable. A forest may be a strong C sink while simultaneously becoming progressively more N-limited. Extrapolating present-day forest C sinks without considering nutrient dynamics may overstate their persistence. Countries relying heavily on LULUCF C sinks in national UNFCCC reporting should consider whether the N required for continued organic matter accumulation is supplied by new external inputs or by redistribution of N already present within forest ecosystems. 5. Policy relevance: climate and nitrogen policy need to be better connected The policy relevance extends beyond forest ecology. In the Nordic countries, forests contribute substantially to national land-sector C balances. At the same time, all three countries are committed to reducing reactive N emissions due to their impact on ecosystems and human health [3, 5]. The Nordic comparison illustrates why this separation is problematic. Reducing N emissions lowers deposition, which is crucial for achieving several environmental objectives such as protection of biodiversity and limiting marine eutrophication. However, if forest C uptake is partly supported by currently enhanced N deposition, or delayed responses to past inputs, future C sink dynamics may be affected. Conversely, if C sequestration is maintained by mining soil N, current climate benefits may be associated with gradual deterioration of ecosystem nutrient status, potentially reducing future sink strength. The analysis does not suggest relaxing N controls to enhance C sequestration, nor does it imply that C sinks are misreported. Rather, it highlights the need for an integrated scientific basis for policy. Current C and N accounting frameworks are designed for different purposes, and their comparison reveals gaps that neither policy covers on its own. 6. Priorities for research and monitoring A key need is analysis of existing long-term forest-soil monitoring data, together with continued, coordinated monitoring of C and N stocks and compartment-specific C/N ratios to quantify spatial and temporal variation and uncertainty. Because soil N pools are large, even small proportional changes may be important yet difficult to detect, making well-designed long-term monitoring essential. The Nordic comparison provides a testable hypothesis: if soil N redistribution supports C accumulation in soils and in biomass, soil C/N ratios should increase over time. Long-term manipulation experiments can clarify how N availability and internal redistribution influence C accumulation and its persistence [21]. Another priority is improved integration of C and N reporting. This requires aligning spatial definitions, separating existing forest from newly afforested land, and assessing whether model-based estimates of soil and dead organic matter stock changes are consistent with N dynamics. Finally, ecosystem models used for policy support should explicitly represent coupled C–N dynamics and distinguish whether C sinks depend on new N inputs, enhanced recycling, or depletion of legacy stocks [22]. 7. Conclusions Reported C-stock increases in Nordic forests imply substantial N accumulation, yet national N budgets show no comparable net N gain and instead indicate net N losses in two of the three countries. This unresolved inconsistency warrants further investigation, as the present analysis cannot determine whether it reflects ecosystem processes, methodological limitations, or both. A possible interpretation is that part of the N supporting current C sequestration is redistributed within forest systems, particularly from soils tao trees. If so, the present C sink may partly rely on internal N capital, making it more uncertain when projected into the future. Analysis of existing long-term forest-soil monitoring data, establishment of new monitoring where needed, and evidence from long-term ecosystem experiments have the potential to resolve this question. A more complete understanding of the nitrogen flows underpinning forest carbon accumulation would strengthen the scientific basis for assessing the future persistence of forest carbon sinks, whether through empirical analyses or coupled C–N models. More broadly, forest carbon and nitrogen stock changes are closely linked, and accounting frameworks would benefit from more explicit integration of these two elements. Better integration between climate reporting, nitrogen budgeting and ecosystem monitoring would strengthen the scientific basis for policy and improve the assessment of forest carbon sink persistence. Acknowledgment This work was supported by the Nordic Council of Ministers (Projects NKL-1915 and NKL-2307), the Swedish Environmental Protection Agency (Naturvårdsverket; Grant Nos. 252-23-004), the Research Council of Finland (Grant Nos. 312559, 345532, and 347848) and the Research Council of Norway (Grant no. 356821). We are grateful to the two anonymous reviewers for their constructive comments. Data availability statement All data that support the findings of this study are included within the article (and any supplementary files). Supplementary data available at https://doi.org/10.1088/1748-9326/aeb70e/data1.

Radware Expands DDoS Protection for Global Cloud Provider

Reported Wednesday, Oct 28 - 6:09am EDT (TheFly subscription required to read more.)