Earths Future最新文献

{"title":"Barrier or Enabler? Cross-Cultural Evidence on Cognitive Biases in Climate Protection","authors":"D. Moser,&nbsp;C. Vance,&nbsp;J. Collard,&nbsp;M. Rieger,&nbsp;E. Anggraini,&nbsp;A. Merico,&nbsp;A. Schlüter","doi":"10.1029/2025EF007697","DOIUrl":"https://doi.org/10.1029/2025EF007697","url":null,"abstract":"<p>There is widespread speculation that cognitive biases pose severe barriers for humankind's ability to engage in climate change mitigation. However, the real-life significance of such effects is a matter of debate, and is likely to be subject to the bias-modifying factor culture. The claims nonetheless imply a testable hypothesis: higher levels of cognitive biases should be predictive for lower willingness to pay (WTP) for climate change mitigation measures in a variety of settings including revealed or stated preference approaches. This study tests this hypothesis using a stated preference approach with university students from Germany and Indonesia. Our analysis proceeds in two steps, beginning with measuring four cognitive biases in each participant using a battery of pre-tested psychological scales. We subsequently implement a contingent valuation experiment eliciting WTP to mitigate sea level rise, allowing us to examine how WTP varies with the extent of cognitive bias. The results provide limited support for the hypothesis. Two of the four biases examined—Risk-Seeking in Losses and Present Bias—do not significantly predict WTP. Loss Aversion is a (moderate) negative predictor in the German sample, whereas Positive Illusion is a positive predictor in the Indonesian sample. Summarily, cognitive biases predict mitigation behavior; however, only in a minority of cases, and where they do, the prediction does not necessarily have to be negative. These results suggest that the impacts, if any, of cognitive biases are complex and context-dependent, warranting careful case-by-case investigation.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007697","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fine-Scale Population, Emissions, and Atmospheric Dynamics Drive Health Disparity Outcomes From Energy Transition","authors":"Xinyuan Huang,&nbsp;Jinyu Shiwang,&nbsp;Klaus Keller,&nbsp;Wei Peng","doi":"10.1029/2025EF007767","DOIUrl":"https://doi.org/10.1029/2025EF007767","url":null,"abstract":"<p>Transitioning to a low-carbon energy system can provide air quality and health co-benefits. While the aggregate effects are intuitively clear, the distributions across subnational regions and population groups and their drivers are complex and less intuitive. Here we use an integrated energy-atmospheric-health modeling framework for the United States to analyze what drives the distribution of health-co-benefits caused by energy transitions. We find that the nationwide health effects mainly depend on macro-scale factors, while the disparity outcomes are further affected by micro-scale factors related to emissions, atmospheric processes, and population vulnerability. For instance, in a Net-Zero 2050 scenario, prioritizing emission reductions near minority populations reduces the national average White-Black disparity in ambient PM_2.5 exposure to 0.2 μg/m³, compared with 0.6 μg/m³ when emission reductions follow current spatial patterns. Using race-specific rather than uniform exposure-response relationships doubles the estimated White-Black disparity in PM_2.5 attributable mortality rates under both Net-Zero scenarios. Our results highlight the importance of resolving fine-scale patterns to understand the distributional effects of energy transitions on pollution and health.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 9","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007767","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148823129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grazing Enhances System Carbon Balance via the Soil-Plant-Livestock Carbon Pump Regulation Despite Suppressing Specific Carbon Cycling Pathways","authors":"Yi Zhou,&nbsp;Xinzhou Zhao,&nbsp;Lan Li,&nbsp;Fujiang Hou,&nbsp;Zhibiao Nan","doi":"10.1029/2026EF008382","DOIUrl":"https://doi.org/10.1029/2026EF008382","url":null,"abstract":"<p>Grazing is among the most direct and effective strategies for anthropogenic regulation of carbon cycling in global grasslands. Through a 24-year grazing experiment, we propose a conceptual framework of the “Soil-Plant-Livestock Carbon Pump” to elucidate the mechanisms underlying grazing effects on carbon cycling within plant, soil, livestock, and soil-plant-livestock system. Our results indicate that although each unit increase in grazing intensity reduced carbon in above-ground standing biomass and litter by 4.91 and 0.91 g C m⁻² yr⁻¹, respectively, grazing ultimately had a significant positive effect on system carbon balance. Specifically, grazing reconfigured the pathways of plant carbon allocation, soil carbon inputs, and livestock carbon consumption. Further analysis revealed that plant and soil carbon cycling pathways were the key direct factors regulating system carbon balance, while livestock indirectly explained 10.6%–44.9% of the variance. Furthermore, from a holistic system perspective, grazing constrained the system carbon pump efficiency, which in turn negatively regulated the carbon balance, accounting for 32%–61% of the variance. These findings indicate that grazing can regulate system carbon balance through the soil-plant-livestock carbon pump. Understanding the operating mechanisms of the system carbon cycle is crucial for developing a dual ecological and economic growth strategy.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 9","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008382","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148823202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Triple-Benefit Potential of Desert Wind Farms in China: Energy, Resource Complementarity, and Climate Effect","authors":"Naijing Liu,&nbsp;Huaiwu Peng,&nbsp;Lixiao Zhang,&nbsp;Liwei Zhang,&nbsp;Donghai Wu","doi":"10.1029/2026EF008179","DOIUrl":"https://doi.org/10.1029/2026EF008179","url":null,"abstract":"<p>The deserts of Northwest China are one of the most wind energy resource rich area in the country, and are characterized by concentrated solar energy and fragile ecosystems. Thus, efforts to harvest wind energy for carbon neutrality goals face vital challenges, such as determining where to site wind farms with consideration of wind energy output, grid stability, and ecological impacts. Existing studies predominantly focus on power generation and economic aspects, and few have proposed a multidimensional framework that simultaneously optimizes energy generation, wind-solar complementarity for grid integration, and climate impacts. To address this gap, we develop an assessment framework that integrates the Weather Research and Forecasting model, geostationary satellite observations, and machine learning models. Utilizing our framework, we identified an optimal area of 219,000 km² that can generate 3,165 TWh of electricity annually. This optimal area also has high wind-solar complementarity (correlation coefficient: −0.81) and can reduce the diurnal land surface temperature range by 0.5°C. Our framework may provide benefits for all three objectives: providing considerable electricity, strengthening the stability of the grid, and helping reduce the temperature range. Our analysis reveals spatial heterogeneity with distinct characteristics: Inner Mongolia excels in terms of energy economic benefits, while the wind farms on the Tibetan Plateau offer stronger climatic effects. This triple benefit framework advances beyond a single-objective siting framework and provides a practical framework for sustainable energy planning under multiple constraints.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 9","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148823213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of Global Sea-Level Rise Projections and Their Uncertainty","authors":"Andra J. Garner,&nbsp;Amy Appollina,&nbsp;Jessica Slotter,&nbsp;Gregory G. Garner,&nbsp;Aimée B. A. Slangen,&nbsp;Robert E. Kopp,&nbsp;Benjamin P. Horton","doi":"10.1029/2025EF007836","DOIUrl":"https://doi.org/10.1029/2025EF007836","url":null,"abstract":"<p>For more than 40 years, scientists have projected future sea-level change. Documenting how sea-level projections have evolved is vital for tracking progress, uncertainties, and future research needs. Here, we update and analyze a database of global-mean sea level (GMSL) projections dating from 1982 to 2025, identifying five key findings. First, GMSL projection generation has been concentrated in a small number of developed countries, with 95% of projections produced in the United States, United Kingdom, European Union, or Australia. Second, while GMSL projections for 2050 and 2100 have been published regularly since the early 1980s, only 30 of 103 studies have produced projections extending beyond 2100; all but one of these 30 studies postdates 2010. Third, among studies providing multiple estimates, the range of highest GMSL projections for 2100 has broadened since 2007, reaching 0.6–2.0 m across publications since the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Fourth, GMSL projections from the IPCC have historically been conservative compared to projections from individual studies. Prior to AR6, ∼66% of 2100 projections at the upper end of uncertainty intervals from individual studies exceeded the corresponding upper projections from IPCC reports. However, the inclusion of “low-confidence” GMSL projections in AR6 to assess higher amounts of GMSL change of poorly known likelihood reduces this problem: the 83rd percentile of these low-confidence projections is exceeded by &lt;25% of upper estimates from individual studies. Finally, analyses suggest that the arrival time of key GMSL milestones are often similar for projections spanning multiple eras and using various methodologies.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007836","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking Grain Planting Patterns to Multidimensional Agricultural Sustainability: Evidence From Landscape Metrics and Spatial Analysis in China","authors":"Ruihua Shen,&nbsp;Kaixuan Wang,&nbsp;Yulian Xia,&nbsp;Shikun Sun,&nbsp;Jingxin Sun,&nbsp;Yali Yin,&nbsp;Yubao Wang,&nbsp;Pute Wu","doi":"10.1029/2025EF008035","DOIUrl":"https://doi.org/10.1029/2025EF008035","url":null,"abstract":"<p>Changes in grain planting patterns have been closely linked to substantial increases in crop yields. However, their relationships with the Sustainable Development Goals (SDGs) remain unclear, particularly across multiple SDG dimensions. Clarifying these relationships could help inform progress toward food security and the SDGs. Hence, this study develops a comprehensive research framework to evaluate grain planting patterns, quantify seven agriculture-related SDGs grouped into four dimensions—economic, social, ecological, and water-resource sustainability—and analyze their spatiotemporal dynamics and links with planting patterns. Using Geodetector, Spearman correlation, and Geographically and Temporally Weighted Regression (GTWR), we quantify links between planting patterns (area, yield, landscape metrics) and agricultural SDG scores standardized to a 0–100 scale, with higher values indicating better relative performance within the assessment framework. Over 20 years, grain production increased by 53.47%, corresponding to a 210.44 Mt increase on a 15.04 Mha expanded planting area. Water-resource and ecological dimensions had higher normalized SDG scores, with multi-year averages of 60.16 and 59.27, respectively, than the economic (48.12) and social dimensions (44.80). SDG scores increased to varying degrees during the study period, except for the social dimension, which remained relatively stable. Farmland expansion and greater landscape complexity were positively associated with economic and social SDG scores, but negatively associated with ecological and water-resource SDG scores. These findings highlight potential trade-offs between productivity gains and multidimensional sustainability and provide evidence for SDG-oriented agricultural management.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF008035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148785199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What SAR Labels Hide About a Changing Arctic","authors":"M. Mahmud","doi":"10.1029/2026EF008828","DOIUrl":"https://doi.org/10.1029/2026EF008828","url":null,"abstract":"<p>Synthetic aperture radar (SAR) has been the backbone of Arctic sea ice monitoring since the 1990s, yet nearly every operational product that assigns an ice class or geophysical state (melt onset dates, freeze-up timing, ice-type classifications) is derived by compressing continuous radar backscatter into discrete categorical labels. This Commentary argues that such compression is not merely a simplification but a systematic loss of physical information that increasingly compromises trend attribution and cross-sensor synthesis as the Arctic transitions from a perennial to a seasonal ice regime. A semi-empirical forward-model demonstration shows that physically distinct ice states can produce indistinguishable C-band backscatter yet separate cleanly at L-band, confirming that single-frequency categorical detection is fundamentally non-unique. The multi-frequency SAR constellation now in orbit (Sentinel-1 and RCM at C-band, NISAR at L- and S-band) provides the measurement basis to move beyond labels toward physically based retrieval. A Bayesian inversion framework that outputs continuous state estimates with formal uncertainty bounds could preserve backward-compatible categorical products for operational ice services while adding the process-level traceability that climate science demands. Realizing this architecture requires coordinated investment in multi-frequency forward models, designated Arctic supersites, and in situ campaigns targeting the snow microstructure variables that remain the largest source of retrieval ambiguity.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008828","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148785184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate-Induced Severe Water Scarcity Events as Harbingers of Global Wheat Price","authors":"Miroslav Trnka,&nbsp;Jan Meitner,&nbsp;Jan Balek,&nbsp;Song Feng,&nbsp;Juliana Arbelaez Gaviria,&nbsp;Milan Fischer,&nbsp;Esther Boere,&nbsp;Petr Havlík,&nbsp;Kurt-Christian Kersebaum,&nbsp;Claas Nendel,&nbsp;Margarita Ruiz-Ramos,&nbsp;Daniela Semerádová,&nbsp;Mikhail A. Semenov,&nbsp;Markéta Poděbradská,&nbsp;Jan Esper,&nbsp;Ulf Büntgen,&nbsp;Max Torbenson,&nbsp;Jáchym Brzezina,&nbsp;Zdeněk Žalud,&nbsp;Gabriel Katul,&nbsp;Jørgen E. Olesen","doi":"10.1029/2025EF006095","DOIUrl":"https://doi.org/10.1029/2025EF006095","url":null,"abstract":"<p>This study connects the dots between global extent of severe water scarcity (SWS) events and spikes in food price. The authors start with three staple crops (rice, wheat, and maize) using a empirical but crop specific characterization of severe water scarcity occurrence, which is defined based on the area of land cultivated with each studied crop that on a given year is under SWS conditions. Water scarcity is estimated based on 1, 3, and 12 months standardized precipitation evapotranspiration index during crop specific sensitive periods (SPs). SPs coincide with the 4 months prior to harvest. A SWS-wheat price relationship model was developed for period 2001–2021 and tested for 1986–2000 and 2022–2024 with future projections calculated under climate change using climate model simulations from CMIP5 and CMIP6 up to 2100. The results show a marked increase in wheat prices driven by increasing SWS area, which is in turn a function of greenhouse gas emissions. The results indicate that the meanglobal mean temperature increase by 3°C (compared to 1951–1980) could lead to the tripling of the mean global wheat price compared to 2010 (after deflating).</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF006095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148785028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pervasive Building Height Thresholds for Urban Heat Response and Implications for Climate Mitigation","authors":"Wenting Yan,&nbsp;Yongxian Su,&nbsp;Shiqi Jin,&nbsp;Chaoqun Zhang,&nbsp;Xuhui Lee,&nbsp;YuYu Zhou,&nbsp;Philippe Ciais,&nbsp;Chi Xu,&nbsp;Wenjian Hua,&nbsp;Ziyin Liao,&nbsp;Yixiao Wang,&nbsp;Timon McPhearson,&nbsp;Steward Pickett,&nbsp;Raffaele Lafortezza,&nbsp;Weiqi Zhou","doi":"10.1029/2026EF008383","DOIUrl":"https://doi.org/10.1029/2026EF008383","url":null,"abstract":"<p>Urbanization is accelerating vertical urban development, yet the complex relationship between building height (BH) and urban heat island (UHI) intensity remains underexplored. Using 30-m high-resolution urban building data from 2005 to 2020, we quantify the impact of BH on UHI across 11,290 urban grid cells in 331 Chinese prefecture-level cities and assess the potential for UHI mitigation through BH composition reorganization. Our analysis reveals a critical BH threshold (BH_crit) that marks a shift in the thermal effect of BH. Below BH_crit, increasing BH intensifies UHI effects; beyond this threshold, further height increases result in cooling—a finding that challenges the conventional assumption that taller buildings consistently exacerbate urban heat. We further project that, in principle, China's urban grid cells could reduce UHI intensity through BH reorganization, with a national average mitigation potential of 0.31 ± 0.004°C. These findings underscore the importance of optimizing vertical urban composition as a proactive UHI mitigation strategy and provide valuable insights for sustainable urban densification from a three-dimensional perspective.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EF008383","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Pest Traps to Management Maps: Predicting the Abundance and Phenology of Japanese Pine Bast Scale to Guide National Forest Adaptation and Timely Control","authors":"Seon-Woo Bang,&nbsp;Seunguk Kim,&nbsp;Il Nam,&nbsp;Jae-Woo Lee,&nbsp;Ji-Hong Park,&nbsp;Min-Woo Lee,&nbsp;Uirin Ha,&nbsp;Jong-Kook Jung,&nbsp;Sora Kim,&nbsp;Yong-Hun Kim,&nbsp;Man-Gi Lee,&nbsp;Sang-Gil Lee,&nbsp;Seong-Cheol Moon,&nbsp;DongWoon Lee,&nbsp;SangMyeong Lee,&nbsp;Ghiseok Kim,&nbsp;Suk-Ju Hong,&nbsp;Hyeyeong Choe,&nbsp;Il-Kwon Park","doi":"10.1029/2025EF007552","DOIUrl":"https://doi.org/10.1029/2025EF007552","url":null,"abstract":"<p>Forest insect outbreaks are intensifying under climate change and global trade, yet their spatiotemporal dynamics remain poorly quantified. This lack of predictive understanding limits timely and effective management. The Japanese pine bast scale (<i>Matsucoccus matsumurae</i>), which has persisted in South Korea for more than 50 years despite ongoing control efforts, exemplifies this challenge. We developed the first national framework that converts raw monitoring data into spatially explicit forecasts of pest abundance and phenology. A nationwide pheromone-trap network (164 sites in 2022 and 65 in 2023) provided standardized observations of male flight activity. Deep learning automated the counting of captured insects, and statistical modeling of biweekly captures yielded the timing of first emergence and peak flight. These data, combined with a 30 m host-abundance map and 1 km environmental predictors, were used to train extreme gradient boosting (XGBoost) models to predict abundance and phenology across South Korea. The models explained 78% of abundance variance and up to 90% of phenological variance. They revealed strong spatial heterogeneity: captures ranged from 0 to &gt;43,000 per trap, were concentrated along southern coasts, while emergence timing differed by up to 9 weeks nationwide. Warmer winters advanced emergence, and stable climates promoted higher abundance. Bootstrap ensembles quantified spatial prediction uncertainty, highlighting regions with low confidence that require intensified monitoring. Our results expose a highly dynamic and uneven infestation landscape that fixed, calendar-based strategies cannot address. By linking large-scale ecological observation with predictive modeling, this framework establishes a data-driven basis for adaptive, climate-resilient forest pest management.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"14 8","pages":""},"PeriodicalIF":8.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EF007552","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}