Search Results (1,999)

Though many food systems on Earth offer benefits to space travelers, their ability to meet the demands of spaceflight remains unestablished. This study examines the application of magnesium oxide-coated halloysite nanotubes (MgO-HNTs), synthesized via electrodeposition, to enhance seed germination and early plant development under Earth, lunar, and Martian soil conditions. Successful surface modification was confirmed by scanning electron microscopy. Growth experiments with Heirloom Cherry Tomato and Golden Tomato seeds were conducted under hydroponic and soil-based conditions and subsequently extended to lunar and Martian regolith simulants. A Response Surface Methodology approach, based on a Box-Behnken Design, evaluated the effects of temperature, MgO-HNT concentration, and light duration on multiple growth responses, identifying seedling length and the root length stress tolerance index (RLSI) as the most responsive indicators of treatment. Optimal conditions (25 °C, 12 h photoperiod, 100 mg/mL MgO-HNTs) produced the greatest increases in root and shoot length in Earth soil. In lunar regolith, optimal root development occurred at 100 mg/mL (root length: 17.7 mm, shoot length: 5.08 mm, RLSI: 141.1%, germination: 80%), whereas Martian regolith peaked at 10 mg/mL (root length: 12.3 mm, shoot length: 4.28 mm, RLSI: 167.9%, germination: 100%), which may be associated with differences in the physicochemical properties of the two substrates. These findings offer preliminary evidence that MgO-HNTs can enhance early plant development across terrestrial and extraterrestrial substrates. As this study was limited to a single crop species under short-term, controlled laboratory conditions without direct physiological or biochemical biomarker measurements, further validation will be required to support broader agricultural or in-situ resource utilization (ISRU) applications. Full article

When national-level market-oriented agricultural reforms enter regional agricultural systems with different land-use structures, production infrastructure, and degrees of institutional dependence, they may generate spatially uneven political responses. Focusing on Punjab and Madhya Pradesh, India, this study integrates agricultural reform policy documents, public procurement statistics, MODIS land-cover data for 2013, 2017, 2020, and 2023, irrigation statistics for the 2013–2014 to 2022–2023 agricultural years, and protest-event records from the Global Database of Events, Language, and Tone (GDELT) Event Database for 25 September 2020 to 11 December 2021. We examine agricultural land-use intensity, cropland fragmentation, gross irrigated area, and the district-level coverage, spatial concentration, and cross-quarter persistence of protest events. Punjab maintained an agricultural land-use intensity of approximately 95%, a cropland patch density of 2.50–4.27 patches per 1000 km², and only a 0.56% increase in gross irrigated area, indicating a mature agricultural space characterized by intensive land use, continuous cropland, and stable irrigation. By contrast, agricultural land-use intensity in Madhya Pradesh increased from 75.24% to 77.63%, cropland patch density declined from 17.40 to 13.15 patches per 1000 km², and gross irrigated area increased by 70.87%, indicating a transitional agricultural space marked by gradual land expansion, increasing cropland connectivity, and rapid irrigation growth. Protest events were more widespread and persistent in Punjab but more concentrated in Madhya Pradesh. These findings show that agricultural land expansion, cropland fragmentation, or irrigation growth alone cannot explain regional differences in farmer protests. Rather, the observed regional differences are more consistent with an interpretation emphasizing the interaction between differentiated agricultural spaces and existing institutional arrangements, including minimum support prices, public procurement, and Agricultural Produce Market Committee markets. The study develops an integrated institutional–spatial framework for explaining uneven regional responses to uniform agricultural reform. Full article

Wheat ideotypes for dense indoor cultivation require compact architecture, maintained reproductive development, and sufficient biomass accumulation with high planting density and restricted rooting space. Milyang54 is an extremely short-stature winter wheat line developed as a candidate for space-efficient cultivation, but its response to indoor cultivation conditions differing in planting density and rooting space has not been characterized. In this study, Milyang54 and Jokyoung were grown with eight tray, pot, and spacing treatments in a speed-breeding greenhouse. These treatments were designed to generate contrasting planting densities and rooting-space conditions, ranging from low-density pot cultivation to high-density plug-tray and 1.5 cm spacing treatments. Agronomic and reproductive traits, shoot and root biomass, and root-to-shoot ratio were evaluated using a two-factor GLM with variety, cultivation treatment, and their interaction as fixed effects. Cultivation treatment significantly affected all measured traits, and significant variety × treatment interactions were detected for most traits. Across treatments, Milyang54 had a markedly lower mean plant height than Jokyoung (25.62 vs. 42.81 cm) but showed greater mean grain number per spike (11.03 vs. 7.51), shoot dry weight (25.85 vs. 21.58 g), and root dry weight (1.69 vs. 0.97 g). The grain-number advantage of Milyang54 was particularly evident in high-density and restricted-rooting-space tray treatments, including the 105-, 128-, and 162-cell trays. Root-to-shoot ratios varied among cultivation treatments, but a high ratio was not consistently associated with greater grain number. These results indicate that Milyang54 combines compact plant architecture with maintained reproductive performance and biomass accumulation under dense indoor cultivation conditions, suggesting its potential value as a compact wheat ideotype for controlled-environment agriculture. Full article

Linear Diophantine fuzzy sets (LDFSs) enlarge the admissible representation space for uncertain information through membership and non-membership degrees together with reference parameters. Existing LDFS aggregation studies have mainly considered weighted, ordered, power-based, and parametric operators, while partitioned aggregation operators that model possible interrelationships within criterion groups remain limited. Maclaurin symmetric mean (MSM) operators capture interactions among criteria, and reducible weighted MSM operators have been developed to preserve idempotency and reducibility properties but have not been extended to a partitioned MSM operator. This study develops an MSM-based aggregation framework for LDFSs, including the linear Diophantine fuzzy MSM (LDFMSM), the linear Diophantine fuzzy partitioned MSM (LDFPMSM), a reducible weighted partitioned MSM (RWPMSM) and its extension to LDFSs, and the linear Diophantine fuzzy reducible weighted partitioned MSM (LDFRWPMSM) operators. LDFMSM performs symmetric k-subset aggregation over the complete criterion set, LDFPMSM restricts joint aggregation terms to criteria within the same predefined partition, and LDFRWPMSM incorporates criterion weights while preserving idempotency and reducibility properties. Theoretical properties and special cases are established. The framework is demonstrated through numerical examples and an illustrative multi-attribute decision-making (MADM) application for an AI-driven precision agriculture platform selection. Sensitivity analyses examine the effects of the interaction parameter, criterion weights and partition structure and reveal systematic changes in the ranking results. Comparative analysis shows that the LDFPMSM can distinguish alternatives that remain tied under globally symmetric aggregation, while the LDFRWPMSM identifies a different best alternative from the benchmark operators, reflecting its joint treatment of criterion importance and within-partition interactions. Full article

Background: Smallholder farmers are at the forefront of climate change, necessitating dynamic, continuous adaptation strategies to safeguard their livelihoods and food systems. Although climate-smart technologies and indigenous knowledge are available, traditional top-down agricultural extension models often fall short in promoting inclusive, community-driven ownership, which is vital for long-term resilience. Objective: This paper investigates how effective knowledge brokering can augment the agricultural extension system—facilitating connections among researchers, extension agents, and smallholder farmers—to maintain climate resilience and foster inclusive, locally led adaptation (LLA). Methods: Drawing on the IDRC–Step Change SCALE project, implemented between August 2025 and May 2026, this study assesses the effect of targeted capacity-building interventions within the extension system. By employing active knowledge-brokering mechanisms such as safe-spaced KIIs, FGDs, co-creation workshops, and capacity-building workshops, the project enabled ongoing, bidirectional learning. This strategy ensured that scientific innovations were adapted into context-specific practices, while indigenous knowledge and local priorities directly influenced ongoing agricultural research. Pre- and post-intervention assessment scores were compared using paired-samples t-tests with exact Wilcoxon signed-rank confirmation, taking the knowledge area as the unit of analysis; differences between training rounds were tested by randomized complete block ANOVA with orthogonal country, phase, and country-by-phase contrasts; and qualitative data from KIIs and FGDs were analyzed thematically. Results: The findings indicate that knowledge brokering transforms the extension system into a responsive foundation for agricultural resilience. Key outcomes include a mean knowledge gain of 53.8 percentage points across the four capacity-strengthening rounds, from 26.5% pre-training to 80.3% post-training (95% CI 51.4 to 56.3; paired t(27) = 44.78, p < 0.001), with improvement recorded in all seven knowledge areas in all four rounds; sustained adoption of climate-adaptive technologies across 1042 participant attendances in Nigeria and Senegal; enhanced participation of marginalized groups, with women accounting for 568 attendances (54.5%) overall, though ranging from 38.9% to 60.2% between rounds; and a clear transition toward self-sustaining, locally led adaptation practices. Conclusions: To effectively confront climate uncertainty, agricultural extension must evolve from a mere information dissemination system into an interactive, knowledge-brokering network. Strengthening this system is a vital, scalable pathway to maintaining inclusive resilience in smallholder agriculture. Full article

Heavy metal contamination of agricultural soils and urban green spaces has become a major environmental concern, threatening ecosystem functioning, food safety, and sustainable land management. Silicon-based growing media have emerged as an environmentally friendly approach for reducing metal mobility while enhancing plant establishment in contaminated environments. Despite growing research interest, a comprehensive evaluation of the mechanisms, effectiveness, and practical applications of silicon-amended growing media across diverse plant systems remains lacking. This systematic review addresses this gap by synthesizing current evidence following the PRISMA 2020 framework. A systematic search of Web of Science, Scopus, PubMed, ResearchGate and Google Scholar identified 247 publications published between 2010 and 2025, of which 32 peer-reviewed studies met the predefined inclusion criteria for qualitative analysis. The reviewed literature demonstrates that silicon incorporation into growing media improves substrate functionality by modifying physicochemical properties, immobilizing heavy metals, regulating metal transport within plants, strengthening antioxidant and osmo-protective defense systems, preserving photosynthetic activity, and improving nutrient acquisition and water-use efficiency. Furthermore, silicon influences molecular signaling pathways and promotes beneficial rhizosphere interactions that collectively enhance plant resilience under metal stress. Among the evaluated materials, silicon nanoparticles consistently exhibited greater remediation efficiency than conventional silicon sources because of their higher surface reactivity and improved bioavailability. Overall, silicon-based substrate engineering represents a multifunctional and sustainable strategy for mitigating heavy metal contamination while improving the performance of agricultural crops and urban vegetation. Future research should focus on validating these findings under long-term field conditions, optimizing silicon formulations for different substrate types and contamination scenarios, evaluating environmental safety, and integrating silicon-based technologies into climate-resilient agricultural practices and urban green infrastructure. Full article

Saline–alkali soils are important reserve resources for agricultural production. In western Jilin Province, China, large areas of saline–alkali land have been reclaimed as paddy fields; however, their carbon cycling responses to long-term rice cultivation and warming remain unclear. Using a space-for-time chronosequence approach, a laboratory incubation experiment was conducted at 15 °C and 25 °C using soils collected from two soil layers (0–20 and 20–40 cm) in fields with 2, 5, 10, and 12 years of rice cultivation, together with an uncultivated reference field (CK). The results showed that cumulative potential soil carbon dioxide (CO₂) production was generally higher in cultivated soils than in CK, peaking at 5 years under 15 °C and at 10 years under 25 °C. It subsequently declined in the 10- and 12-year treatments at 15 °C and decreased slightly at 12 years at 25 °C. Soils with longer rice cultivation histories generally exhibited relatively high apparent temperature sensitivity (Q₁₀) at several stages of incubation, particularly in the 0–20 cm soil layer. Hydrolytic enzyme activities generally increased along the rice cultivation chronosequence, whereas polyphenol oxidase activity showed an overall declining trend, reflecting differences in potential enzymatic capacity for carbon transformation among cultivation duration treatments. Bacterial and fungal alpha diversity was generally higher in cultivated soils, particularly from the 5-year stage onward, and they also differed significantly among rice cultivation duration groups in both soil layers, although the fungal pattern in the 20–40 cm layer was partly influenced by heterogeneous within-group dispersion. Partial least squares path modeling showed that enzyme activity was strongly associated with cumulative potential soil CO₂ production at 25 °C and Q₁₀. These findings indicate that potential SOC mineralization across the rice cultivation chronosequence showed clear temperature-dependent patterns. This study provides insights into carbon cycling and its temperature response in reclaimed saline–alkali paddy soils and may inform their sustainable management under changing temperature conditions. Full article

The central point of evolutionary ecology is understanding the drivers of variation in life-history strategies among organisms. The post-fledging dependence period is a critical life-history stage in the life cycle of altricial birds, influencing their future long-term survival, fitness, and reproduction. This period represents the transition between fledging and the onset of natal dispersal or migration, when offspring are highly dependent on parental care. In this study, we used GPS-GSM telemetry to analyze for the first time the duration of this phase and the size of the ranging area of Lesser Spotted Eagles during the dependence period, testing the importance of various extrinsic (habitat type, territory, region) and intrinsic (body condition, sex, fledging date, fledging age) factors. Our survey was conducted between 2020 and 2025 in Bulgaria, SoutheastEurope. The mean duration of the post-fledging dependence period (PFDP) in the juveniles was 47 ± 5 days (SD) (n = 14). The age of independence of eagles ranged from 71 to 110 days (median = 95 days). Our results show that the fledging date is the main determinant shaping the dependence period both temporally and spatially. The size of the ranging area (90% home range) of juveniles during the PFDP varied from 0.03 to 16.72 km², with a mean value of 2.41 km² ± 4.34 SD (n = 14). Home range was influenced mainly by surrounding habitats (grassland types and forests). In line with our hypothesis, we found that birds are habitat-selective, strongly preferring forests and avoiding human-modified landscapes (infrastructure and agricultural fields) during this early life-history stage. We established a relatively small ranging area inhabited by eagles and a low-mobility pattern with a gradual increase in movements that is highly individual-specific. In general, forests occupied the largest share of the home range of eagles, ranging from 0.38% to 87.45%, with a mean value of 49.47% ± 26.57. The duration of the post-fledging dependence period and the size of the ranging area were constrained by the onset of first migration, coinciding with the beginning of birds’ independence. The home range overlap of eagles varied from 56.35% to 100%, with an average value of 87.94%. The high similarity among ranging areas identified in this study emphasizes the importance and consistency of environmental conditions, such as habitat features, compared to others that would vary yearly. The key aspects (spatial and temporal) of the post-fledging dependence pattern, identified by our study, are important for species conservation and must be integrated into future landscape planning. Our results also contribute to a better understanding of the complex factors shaping raptors’ space-use pattern in this key, a poorly studied life-history trait of raptors, thus enhancing knowledge for similar species of conservation concern. Full article

Urban green spaces play an important role in supporting ecosystem functions, landscape connectivity, and urban resilience; however, their potential contribution may be constrained by fragmentation, inadequate maintenance, and limited integration among spatial planning instruments. This study develops a preliminary green infrastructure (GI) planning framework for the municipality of Noicattaro (Bari, Apulia, Italy) by integrating planning provisions with the observed condition and spatial distribution of existing public green spaces. A GIS-based spatial analysis, complemented by field surveys, assessed 89 public green spaces for compliance with planning requirements and maintenance status. The analysis also considered the spatial structure of the surrounding peri-urban landscape, including the karstic dry valleys (Lame), agricultural land uses, and relevant landscape and hydrogeological planning constraints. The results show that only 20.2% of the surveyed green spaces met both planning and maintenance criteria, whereas 78.4% fell into categories characterised by planning non-compliance, inadequate maintenance, or both. These findings highlight potential gaps between formal planning provisions and the observed condition and management of the municipal green system. The analysis of the Lame further revealed a predominance of agricultural land over natural vegetation, emphasising the importance of considering the wider agricultural and peri-urban landscape when identifying potential ecological connections. Based on the combined spatial and field assessment, a preliminary GI network framework was developed around core ecological areas, buffer zones, and strategically located green spaces, with the aim of identifying potential spatial connections and areas for further investigation. Overall, the study demonstrates the potential of integrating planning analysis, GIS-based assessment, and field observations as a screening and decision-support approach for more context-sensitive GI planning in peri-urban Mediterranean landscapes. The proposed framework should be regarded as a preliminary planning proposal requiring further validation through biodiversity, ecosystem-service, accessibility, and implementation assessments. Full article

Agrivoltaic systems configure photovoltaic power generation and agricultural production within the same land space, providing a new pathway for alleviating the conflict between energy development and farmland conservation; however, array shading and structural constraints also alter crop growth and agricultural equipment operating environments. Following the PRISMA process, this review searched studies published from 2010 to 2026 in the Web of Science Core Collection, Scopus, and China National Knowledge Infrastructure, and ultimately included 206 publications. The review focuses on array-induced environmental reconfiguration, equipment adaptation, light–thermal sensing and prediction, and coordinated agrivoltaic operation. Existing evidence indicates that the environmental effects of agrivoltaic systems are clearly influenced by climate and array configuration; in representative vertical or tracking systems, annual-scale photosynthetically active radiation decreased by approximately 11% to 34%. Mismatch among module height, row spacing, and implement width reduces field-operation efficiency, which fell to approximately 45% under severe mismatch in some experiments; elevated arrays also cause GNSS signal attenuation and increase the difficulty of continuous positioning beneath the panels. Because existing studies differ considerably in site conditions, evaluation indicators, and validation periods, the above results mainly reflect representative performance ranges. Matching criteria between photovoltaic arrays and agricultural machinery have not yet been established, long-term field-measured data in complex field environments are insufficient, model adaptability across regions is limited, and coordinated scheduling of agricultural production and photovoltaic operation and maintenance remains inadequate. Overall, coordinated design of arrays and agricultural machinery, multi-sensor fusion navigation, environmental prediction corrected for array structure, and hierarchical scheduling under safety constraints are the main development directions for intelligent coordinated operation of agrivoltaic systems. Full article

Climate change is altering soil organic carbon stocks and the associated carbon fluxes of cropland ecosystems—including organic matter mineralization, microbial respiration rates, and CO₂ emissions—through shifts in temperature and moisture regimes. Ecosystem respiration, the main pathway linking terrestrial carbon pools to atmospheric CO₂, directly governs the carbon source–sink balance of croplands. As integral components of the agroecosystem, soil microorganisms directly participate in ecosystem respiration and organic carbon transformation: they contribute to heterotrophic respiration through the decomposition of organic matter, while also synthesizing new organic compounds, forming microbial biomass, and promoting organic carbon stabilization, with their community composition and metabolic activity adjusting to changing environmental conditions. To synthesize research progress and clarify how the field has evolved over the past three decades, we analyzed 290 publications (1991–2025) from the Web of Science Core Collection, combining bibliometric tools (CiteSpace 7.0, VOSviewer 1.6.20) with a structured evidence synthesis to map the research landscape, knowledge structure, hotspot evolution, and mechanistic understanding of the microbial processes underlying cropland ecosystem respiration. Publication output has grown steadily, led by China (161 publications; 55.5%) and the United States (47; 16.2%), which together account for 71.7% of the sample. The knowledge structure has coalesced around five core themes (ecosystem respiration, soil microbial communities, soil organic carbon, carbon cycling, and agricultural management), corresponding to 14 major thematic clusters (Q = 0.668, S = 0.778). Rather than strictly sequential stages, these thematic areas developed largely in parallel, with a gradual shift in research emphasis over time: early work centered on fundamental carbon-cycle processes, including soil respiration flux, organic matter decomposition, and CO₂ release, whereas later research increasingly emphasized microbial community structure, functional mechanisms, carbon use efficiency, soil organic carbon stabilization, carbon sequestration, fungal communities, and ecological stoichiometry. The responses of cropland respiration to climate change are context-dependent: under specific conditions their direction and magnitude may be dominated by a single limiting factor, whereas overall they emerge from the coordinated interplay of temperature, moisture, substrate supply, and agricultural management, within which microbial processes play a central but still incompletely resolved role. Future research should prioritize long-term in situ observations, multi-factor coupling experiments, and functional validation of microbial processes, and integrate microbial mechanisms into ecosystem models to strengthen predictions of cropland carbon cycling and support agricultural emission reduction, carbon sequestration, and sustainable management. Full article

Modern smart agriculture increasingly relies on edge computing for real-time, high-concurrency tasks such as wide-area drone-based crop monitoring. However, highly volatile workloads and severe environmental noise in agricultural Internet of Things (IoT) networks often lead to resource congestion and high latency when relying on traditional reactive scheduling. To address these challenges, this paper proposes a hybrid prediction-driven proactive resource scheduling method for edge computing. We construct a Variational Mode Decomposition-Convolutional Neural Network-Attention-Bidirectional Long Short-Term Memory (VMD-CNN-Attention-BiLSTM) model to filter environmental noise and accurately capture the spatio-temporal features of bursty traffic. Furthermore, a deep reinforcement learning scheduling algorithm based on Proximal Policy Optimization (PPO) incorporates future workload trends into its state space, dynamically optimizing task offloading. To evaluate the proposed Predictive Computational Scheduling Framework (PCSF), we developed a custom edge computing simulation environment and synthesized a hybrid dataset combining real-world server logs from the Alibaba Cluster Trace with deep learning inference workloads derived from a Wheat Plant Diseases image repository. Simulations demonstrate that the prediction model achieves a Root Mean Square Error of 0.030 and a Mean Absolute Error of 0.0215. Compared to static and reactive baselines, the PCSF reduces average task timeout violations to 2.2 and total system energy consumption by nearly 40%. This proactive mechanism effectively overcomes decision-making lags, enabling efficient, low-latency computing resource allocation for modern agricultural facilities. Full article

Urbanisation has become a significant driver of ecological transformation, resulting in the degradation of urban green and blue spaces (UGSs and UBSs) and a subsequent decrease in ecosystem services (ESs). It is imperative to evaluate the spatio-temporal dynamics of UGS and UBS in order to develop sustainable urban planning strategies, particularly in the swiftly expanding cities of the Global South. In the Siliguri Planning Area (SPA), India, this study examines the long-term variations in UGS and UBS and their associated ecosystem service values (ESVs) from 1991 to 2021. The Normalised Difference Vegetation Index (NDVI) and Modified Normalised Difference Water Index (MNDWI) were employed to delineate UGS and UBS using multi-temporal Landsat imagery, respectively). The benefit transfer method was employed to quantify ESV, and sensitivity analysis was conducted to assess the valuation’s reliability. Also, adjusted value coefficients were employed. The findings indicated that landscapes such as tea garden (58.74% reduce) and agricultural land (46.09 increase) have undergone a substantial transformation as a result of urbanisation, with the built-up areas increasing from 5798.61 ha in 1991 to 8500.23 ha in 2021 (46.59% increase). Simultaneously, UGS decreased (by 40.26%) from 12,533.04 ha (47.81% oftotal area)in 1991 to 7486.29 ha (28.55% oftotal area) in 2021, while UBS decreased (by 79.47%) from 255.69 ha (0.94% oftotal area) in 1991 to 52.48 ha (0.19% oftotal area) in 2021. Subsequently, the ESV of UGS and UBS fell significantly from 1183.05 crores (INR) to 706.67 crores (INR) and 34.72 crores (INR) to 7.12 crores (INR), respectively. This confirms the elasticity of the valuation estimates, as the sensitivity coefficients remained below one. The study contributes to understanding the crucial role of urban planners, private property owners, and builders in promoting green–blue infrastructure conservation, wetland restoration, and ecological zoning. Such ecosystem service-based planning is essential for achieving sustainable development in rapidly urbanising regions and enhancing urban ecological resilience. Full article

Plants have coevolved with microbes for nearly 500 million years; however, their interrelationship is not well understood. Plant roots have an intricate relationship with soil microbes. Such relationships mold the growth, development, immunity and physiology of plants and thus are of immense interest to agriculture and the environment. Technological advancements in sequencing, imaging, omics, synthetic biology and artificial intelligence have allowed scientists to dissect such relationships to a higher resolution. Thus, these advances have facilitated a deeper understanding of plant–microbe interactions and their role in the life cycle of plants and the environment. However, factors such as microbial diversity, microbial abundance, heterogeneity of soil and plasticity of the environment have precluded a clear in situ understanding of microbial community structure. Thus, constructing synthetic microbial communities or SynComs and investigating their effect on plants in a controlled environment offers a reductionist and manageable approach to understand plant–microbe relationships. This approach reduces the confounding variables present in the natural environment and facilitates the understanding of such complex interactions. Members of such communities are identified using 16S rRNA sequencing and are constructed using few microorganisms; often fungal strains are added for cross-kingdom SynComs. Metabolic modeling, metabolic cross-feeding along with ecological and evolutionary principles, can be used while choosing candidates for SynComs. Scalability, transferability, reproducibility, predictability and stability are the major bottlenecks in SynCom research. This emerging area of science may have transformative impact in agriculture, environment and space colonization. In this article, we present our perspective on the latest advancements, challenges and future potential of this technology. Full article

This study examines the socio-spatial dynamics of rural overtourism and landscape commodification in a peripheral municipality in Northwestern Italy. Employing a qualitative, longitudinal ethnographic design, data were collected between May 2020 and October 2021 in San Giovanni (Piedmont). The methodology combined extensive participant observation in public, commercial, and agricultural spaces with ethnographic interviews with six stakeholder groups: local promoters, municipal administrators, professional farmers, long-term residents, shopkeepers, and visiting tourists. Qualitative data were processed using inductive thematic analysis. The results indicate that visitor surges were initiated endogenously by local promoters through the installation of an open-access, gamified “Big Bench” attraction designed to counter long-term demographic and economic contraction. The influx of day-trippers generated localized spatial intrusion, traffic congestion, and physical disruptions to agricultural operations during peak harvest periods, as well as to residents’ daily activities. Rather than driving generalized economic revitalization, the intervention produced host–visitor friction and intra-community polarization between local promoters seeking external visibility and residents experiencing spatial disruptions and loss of privacy. The study demonstrates that overtourism can develop endogenously through promoter-led self-commodification and provides a three-tiered governance framework encompassing policy, destination management, and community-level strategies for fragile rural territories. Full article