Mountainous Regions Research Articles

The 3rd Hutchinson lecture: numerical modelling of forests with uprooting as a nature-based solution to mitigate flow-type landslides

AbstractTo protect human lives and infrastructure in mountainous regions from flow-type landslides, engineered countermeasures, such as rigid and flexible barriers, are installed along predicted flow paths. Over recent years, research efforts in physical and numerical modelling have helped advance the understanding of impact mechanisms involved and enabled the optimization of the design of engineered solutions. With the advent of sustainable engineering, attention has shifted towards the use and development of nature-based solutions to impede flow-type landslides. A simple nature-based solution is to consider the effects of forests on the mobility of flow-type landslides. However, to leverage forests, the complex flow-stem interactions and effects of uprooting need to be captured. In this paper, details and results of a new GPU-empowered MPM-LSDEM numerical solver that simulates the effects of flows through tree stems that can uproot are presented along with systematic evaluation of the solver. Simulations of flow-forest interaction with and without uprooting show that forests have profound effects on flow forest interaction. For dense forests, uprooted stems can push flow material to enhance its runout distance. Additionally, uprooted stems tend to concentrate near the front of the flows even if they were evenly distributed throughout the model forest at the beginning. The impact force exerted by a stem can be considered concentrated loading and can damage barriers along the flow path. Taken together, hazard assessment tools that can model the effects of uprooting are crucial to close predictions of hazard extent (i.e., runout distance) and the design of physical countermeasures such as barriers.

The Impact of a Guardianship Social Worker on Inpatient Time-To-Guardianship and Costs: Preliminary Findings.

Unrepresented patients who lack decision-making capacity can remain in hospitals for weeks awaiting guardianship and subsequent discharge, resulting in medically unnecessary and costly extended stays. The guardianship process is complicated and requires collaboration between the medical and legal systems. The Rocky Mountain Regional Veteran Affairs Medical Center created a guardianship social worker position to improve the guardianship process by developing subject matter expertise, infrastructure, and standardized procedures. In this brief report, we provide preliminary data on the impact of a guardianship social worker. Time to guardianship completion, mean lengths of stay (LOS), counts of completed guardianships, and cost estimates were compared before and after the guardianship social worker position was created. The mean time to complete guardianships decreased from 121.9 to 69.8 days (p = .13), the mean LOS for patients awaiting guardianship decreased from 129.8 to 117.2 days (p = .39), and the yearly counts of completed guardianships increased from 2 to 9 (p = .002). Estimated inpatient cost savings per patient was $56,244. While promising, these preliminary data are limited by small case numbers and the unknown impact of the COVID-19 pandemic on long-term placement. Creating guardianship-focused social work positions has the potential to create efficiencies in the guardianship process.

Genetic Diversity and Ecogeographical Niche Overlap Among Hybridising Ox-Eye Daisies (Leucanthemum, Asteraceae) in the Carpathian Mountains: The Impact of Anthropogenic Disturbances.

Climate change and human influence are transforming mountain ecosystems, significantly impacting species distributions and biodiversity. Among these changes, the upward migration of lowland species into mountain regions stands out. This study examines the ecogeographical niche overlap and genetic diversity among three Leucanthemum species distributed along an altitudinal gradient in the Carpathian Mountains: the lowland L. ircutianum (4x), the montane L. rotundifolium (2x) and the alpine L. gaudinii (2x). By genotyping over 600 individuals using SNP analysis, followed by principal coordinate analysis (PCoA), Neighbour-Net Network and Structure clustering, we reveal not just distinct genetic groups but also hybridisation across all species, suggesting the potential for triple hybrids. Genetic admixture is further supported by environmental background and niche overlap analyses that reveal substantial overlap among species, particularly in line with their vertical distribution. Climate envelope plots indicate a likely reduction in available habitat for mountainous species due to climate change, leading to an increase in competition and an intensification of hybridisation. Anthropogenic influences are further intensifying these hybridisation trends. Among the studied species, L. gaudinii is most at risk of overwhelming hybridisation, whereas L. ircutianum may experience habitat expansion. By providing a comprehensive genetic and ecological overview, our research highlights the significance of hybridisation in biodiversity conservation and the challenges posed by environmental changes and anthropogenic activities in mountain environments. This study not only contributes to the understanding of genetic diversity in the Carpathians but also underscores the broader implications for molecular ecology and conservation strategies in mountain ecosystems.

Niche Theory and Species Range Limits Along Elevational Gradients: Perspectives and Future Directions

Despite two centuries of research, the mechanisms underlying the formation of species’ elevational range limits remain poorly understood. The climatic variability hypothesis highlights the role of climatic conditions in shaping species’ thermal tolerance and distribution ranges, while the species interactions–abiotic stress hypothesis underscores the relative importance of biotic factors and abiotic stress along environmental gradients. We emphasize Darwin's perspective on the ubiquity of interspecific competition across climatic gradients and the importance of understanding how climate modulates biotic interactions to shape species distributions. Niche theory provides a comprehensive framework, combined with empirical research, to explore how environmental gradients influence species traits, leading to context-dependent species interactions that constrain distributions. In particular, the application of the concept of environmentally weighted performance can further elucidate these complex ecological mechanisms. Future research should integrate multiple approaches, including field and laboratory manipulative experiments, theoretical modeling, and interdisciplinary collaboration, to improve our understanding of species distributions in mountain regions and to inform biodiversity conservation strategies in the face of rapid environmental change.

La Disponibilidad de cuarzo apto para la talla en las Sierras Pampeanas Australes

This paper presents the results of the study on the availability and use of quartz suitable for flintknapping in the Ongamira Valley (Córdoba, Argentina. At the archaeological sites studied—which correspond to late Holocene hunter-gatherer groups (ca. 1900-3600 BP)—more than 90% of the lithic assemblages were quartz. Researchers articulated different analysis techniques (remote sensing, prospecting, XRF, XRD and petrographic analyses) to understand the origin and local availability of this raw material. The results reveal the location and abundance of the primary quartz sources, estimate the material quality, and help us comprehend the variability between sources. Based on the data, the paper proposes a methodological model for discussing quartz use in the mountainous regions of Central Argentina and its integration into interpretations of human mobility circuits.

Trade as a factor of cultural change: the case of Sardinia

The article, based on field research materials, examines from the anthropological and historical standpoints the origins of trade in the inner mountainous regions of Sardinia, considering it as a factor in changing the worldview of the population of this closed pastoral area. I discuss the specifics of artisanal, domestic, and mainly small-scale commerce and its agents, as well as the range of goods, the attitudes of the locals towards the sellers, etc. I further analyze in comparative terms the aspects of the vision of space and movement in the eyes of the pastoral and peasant populations and the merchants. I argue that the differences between the former and the latter in many ways influenced both the perception of commercial activities in the peasant milieu and the relationship between this milieu and the commercial strata. The research offers novel interpretations, since the issue of endogenous metamorphoses of traditional society, such as that of Sardinia in particular, has not been thoroughly studied up to date in the light of trade processes. Moreover, the research outcomes are relevant due to the fact that many aspects of commerce that had originated in ancient times can be still observed in the present-day trade relations of the region.

A Spatial Landslide Risk Assessment Based on Hazard, Vulnerability, Exposure, and Adaptive Capacity

Landslides threaten human life, property, and vital infrastructure in most mountainous regions. As climate change intensifies extreme weather patterns, the landslide risk is likely to increase, resulting in challenges for disaster management, sustainability development, and community resilience. This study presents a comprehensive framework for assessing landslide risk, integrating advanced machine learning models with the Iyengar–Sudarshan method. Our case study is Son La province, the Northwest region of Vietnam, with data collected from 1771 historical landslide occurrences and fifteen influencing factors for developing landslide susceptibility maps using advanced ensemble machine learning models. The Iyengar–Sudarshan method was applied to determine the weights for landslide exposure, vulnerability, and adaptive capacity indicators. The resulting landslide risk map shows that the highest-risk districts in Son La province are located in the central and northeastern regions, including Mai Son, Phu Yen, Thuan Chau, Yen Chau, Song Ma, and Bac Yen. These districts experience high landslide hazards, exposure, and vulnerability, often affecting densely populated urban and village areas with vulnerable populations, such as young children, the elderly, and working-age women. In contrast, due to minimal exposure, Quynh Nhai and Muong La districts have lower landslide risks. Despite having high exposure and vulnerability, Son La City is situated in a low-susceptibility zone with high adaptive capacity, resulting in a low landslide risk for this region. The proposed framework provides a reference tool for mitigating risk and enhancing strategic decision making in areas susceptible to landslides while advancing our understanding of landslide dynamics and fostering community resilience and long-term disaster prevention.

Soil Acidification and Its Temporal Changes in Tea Plantations of Guizhou Province, Southwest China

ABSTRACTSoil acidification is a significant problem in intensive agricultural systems, particularly in tea plantations. Guizhou province, located in the center of the karst mountainous region of southwest China, has the largest tea plantation area in China. However, the soil acidification characteristics in the tea plantations of Guizhou province, as well as their temporal changes, have not yet been adequately studied. Therefore, soil acidification and associated soil properties in the major tea‐planting counties of Guizhou province were extensively assessed, and the temporal changes in soil acidity over the past 11 years were also evaluated through long‐term and short‐term experiments. The results showed that the average soil pH in the tea plantations in Guizhou province varied from 4.08 to 4.87, with a mean of 4.47. The average cation exchange capacity (CEC), TEA (total exchangeable acidity, TEA), EH (exchangeable H+), and EA (exchangeable Al3+) values were 9.6, 3.7, 5.8, and 19.0 cmol/kg, respectively. Seasonal changes in tea plantation soil pH were observed in low‐ and moderately acidic soils but not in highly acidic soils. The soil pH values did not significantly change during three consecutive years of in situ observations but significantly decreased over the past 11 years at an average of 0.03 yearly. Correlation analysis revealed that the soil pH in tea plantations was significantly positively correlated with the content of specific amino acids, such as glutamic acid, arginine, and valine, but was significantly negatively correlated with certain soil physicochemical properties. The findings of this study indicate that soil acidification in tea plantations of the Guizhou province is severe and possesses distinctive attributes that should be considered for its effective management.

Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model

Abstract. Snow cover modeling remains a major challenge in climate and numerical weather prediction (NWP) models even in recent versions of high-resolution coupled surface–atmosphere (i.e., at kilometer scale) regional models. Evaluation of recent climate simulations, carried out as part of the WCRP-CORDEX Flagship Pilot Study on Convection (FPSCONV) with the CNRM-AROME convection-permitting regional climate model at 2.5 km horizontal resolution, has highlighted significant snow cover biases, severely limiting its potential in mountain regions. These biases, which are also found in AROME numerical weather prediction (NWP) model results, have multiple causes, involving atmospheric processes and their influence on input data to the land surface models in addition to deficiencies of the land surface model itself. Here we present improved configurations of the SURFEX-ISBA land surface model used in CNRM-AROME. We thoroughly evaluated these configurations on their ability to represent seasonal snow cover across the European Alps. Our evaluation was based on coupled simulations spanning the winters of 2018–2019 and 2019–2020, which were compared against remote sensing data and in situ observations. More specifically, the study tests the influence of various changes in the land surface configuration, such as the use of multi-layer soil and snow schemes, the division of the energy balance calculation by surface type within a grid cell (multiple patches), and new physiographic databases and parameter adjustments. Our findings indicate that using only more detailed individual components in the surface model did not improve the representation of snow cover due to limitations in the approach used to account for partial snow cover within a grid cell. These limitations are addressed in further configurations that highlight the importance, even at kilometer resolution, of taking into account the main subgrid surface heterogeneities and improving representations of interactions between fractional snow cover and vegetation. Ultimately, we introduce a land surface configuration, which substantially improves the representation of seasonal snow cover in the European Alps in coupled CNRM-AROME simulations. This holds promising potential for the use of such model configurations in climate simulations and numerical weather prediction both for AROME and other high-resolution climate models.

Interaction regimes of surface water and groundwater in a hyper-arid endorheic watershed on Tibetan Plateau: Insights from multi-proxy data

The interaction between surface water and groundwater is crucial for the management of water resources and the preservation of ecosystems within arid basins, but knowledge on their interaction regimes at the watershed scale remains relatively limited. The present research synthesizes a range of multi-proxy data, including satellite thermal infrared remote sensing, water piezometric level, hydrochemical analyses, and isotopic signatures (2H, 18O and 222Rn), to elucidate the interaction dynamics and patterns between surface water and groundwater within a representative hyper-arid closed basin on Tibetan Plateau. The findings indicate that the water in the basin originates primarily from the glacier/snow melt water and precipitation in the mountainous regions, and would experience multiple but spatially heterogeneous interactions between river and aquifers from the mountain pass to the tail salt lakes after entering the basin. Water interaction in the piedmont alluvial plain is dominated by the pattern of river seepage into aquifers with a water flux of 25.82 m3/s, which drives the development of hierarchical groundwater flow systems in the basin. The interaction pattern converts to groundwater discharge of the local groundwater flow system at the front of alluvial fan plain, which forms the principal spring-fed rivers and the predominant overflow zone in the basin with the groundwater discharge flux of 3.22 m3/s. Most of these discharged groundwaters would infiltrate back into the aquifers in the middle-upper part of the loess plain with the river water leakage flux of 2.89 m3/s. River water and phreatic groundwater present a gradual enrichment of hydrochemcial components and water stable isotopes (2H and 18O) along the flow path due to the intense evaporation in the loess plain. The multiple water interactions between surface water and groundwater lead to the anomalous distribution of fresh water in the middle-lower stream area, which is related to the intermediate groundwater flow system and the local variable groundwater flow system. Water interaction in the lowest salt-marsh plain is in the pattern of regional groundwater flow system discharge into the tail salt lakes under natural condition, but evolves to only discharge into the artificial brine extraction canals rather than the tail salt lakes after decades of brine exploitation. Our findings provide a conceptual and preliminarily quantificational understanding of the interaction regimes between surface water and groundwater in large arid closed basins at the watershed scale.

Drainage estimation across mountainous regions from large-scale soil moisture observations

Drainage is a crucial soil hydrological process that governs the partitioning of rainfall into runoff, groundwater recharge, soil water storage and evapotranspiration. Despite its significance, the drainage process is poorly understood due to the difficulty in direct measurements and insufficient understanding of its underlying physical mechanisms. To address these challenges, we present an innovative, physically-based, data-driven approach, SM2D (Soil Moisture to Drainage), to estimate drainage. SM2D was applied and examined using soil moisture data from a large-scale observation network over mountainous areas during 2014–2020. The soil moisture threshold governing drainage initiation proves to be significantly lower than the commonly employed field capacity metric in hydrological models. This threshold is influenced by factors such as mean soil moisture, bulk density, residual soil moisture, soil organic carbon, and parameters n and α of soil retention curve. Notably, field capacity has minimal impact on this threshold. Additionally, our analysis reveals that the drainage process is more influenced by the Soil Water Storage Increment (SWSI) than by mean soil moisture (MSM) that has traditionally been recognized as a key factor in drainage control. In comparison to commonly used exponential equations and those in models such as the Soil & Water Assessment Tool (SWAT), SM2D demonstrates superior performance in estimating drainage. The exponential equation derived from the SWSI outperforms those derived from other soil moisture metrics, including the commonly utilized MSM, challenging prevailing norms in drainage equations. SM2D holds the potential to generate extensive drainage datasets from satellite or large-scale soil moisture observations, advancing large-scale hydrological studies.

Environmental Assessment of Organic Dairy Farms in the US: Mideast, Northeast, Southeast, and Mountain Regions

Environmental Assessment of Organic Dairy Farms in the US: Mideast, Northeast, Southeast, and Mountain Regions

Integrating Multisource Data and Machine Learning for Supraglacial Lake Detection: Implications for Environmental Management and Sustainable Development Goals in High Mountainous Regions

The accurate detection and monitoring of supraglacial lakes in high mountainous regions are crucial for understanding their dynamic nature and implications for environmental management and sustainable development goals. In this study, we propose a novel approach that integrates multisource data and machine learning techniques for supra-glacial lake detection in the Passu Batura glacier of the Hunza Basin, Pakistan. We extract pertinent features or parameters by leveraging multisource datasets such as radar backscatter intensity VH and VV parameters from Sentinel-1 Ground Range Detected (GRD) data, near-infrared (NIR), NDWI_green, NDWI_blue parameters from Sentinel-2 Multi-spectral Instrument(MSI) data, and surface slope, aspect, and elevation parameters from topographic data. The entire dataset is partitioned into training and testing sets, with machine learning models including the artificial neural network (ANN), the support vector machine (SVM), logistic regression (LR), random forest (RF), and K-nearest neighbour (KNN) trained on the training data (70%). Accuracy assessment employs testing data and involves the evaluation of metrics such as ROC curves and confusion matrices. The best-performing model, ANN, is validated against manually digitized lake polygons derived from Sentinel-2 and Google Earth Pro imagery. Furthermore, the digitized lake polygons are used to analyze glacial lake dynamics from 2016 to 2022. Key findings of this research presented that the NDWI_green, Sigma0_VH, and elevation are the most significant predictors in detecting supra-glacial lakes. Among the various trained and evaluated models, the Artificial Neural Network (ANN) achieved the highest performance (accuracy: 95%, AUC: 0.99) and accurately mapped supra-glacial lakes regardless of their small size. The findings have significant implications for understanding glacial lake behavior in the context of climate change and informing future research and monitoring efforts.

Professional development for ethnic minority public leaders in the Northern mountain regions of Vietnam: needs and barriers to their participation

ABSTRACT This article responds to the research literature gap in professional development (PD) for Vietnamese ethnic minority leaders. Thematic analysis of 32 interviews with ethnic minority public leaders from the northern mountain regions identified PD needs of leaders from disadvantaged backgrounds including (i) ideological and political training, (ii) contemporary issues in local communities, (iii) diversity and inclusion training, and (iv) leadership skills. Three key barriers to their participation in PD were also found, namely (i) poor learning environment, (ii) lack of community engagement experience, and (iii) limited government and employer support. This study underscored that northern mountain ethnic minority leaders encounter ‘mountainous challenges’ when participating in PD activities. The paper concluded with strategies towards more effective PD for ethnic minority leaders in the northern mountain regions of Vietnam. The article carries practical and policy implications for PD developers as well as ethnic minority researchers and practitioners.

Investigation of Lineament Extraction: Analysis and Comparison of Digital Elevation Models in the Ait Semgane Region, Morocco

An automated lineament extraction model was successfully applied in the mountainous region of Ait Semgane, Morocco, enabling the identification of geological and tectonic linear features. Our research implemented several approaches including Topographic Position Index (TPI), shading, and Digital Elevation Models (DEMs), as input for the lineament extraction algorithm and applied to various Dems. We aimed to compare all of these strategies to determine the optimal method and the most favorable input DEM. Results revealed variable performance among methods, emphasizing the importance of choosing the optimum method based on specific objectives. TPI and Hillshade methods showed high sensitivity in detecting lineaments, while ALOS PALSAR and Sentinel 1 InSAR datasets were effective for subtle features. Lineament density exhibited specific orientations for highly-dissected zones, with TPI highlighting NE-SW and E-W orientations. Lineament orientations demonstrated consistency with established geology, confirming pre-existing tectonic knowledge. Cartographic analysis of faults emphasized the success of the SRTM DEM model with the TPI method, highlighting significant faults. Results also revealed a concentration of faults in the NW and southern sectors, corroborating bibliographic references and the well-documented tectonic setting of the study area. This automated methodology facilitated lineament extraction in unmapped areas, reinforcing the validity of the undertaken cartographic analysis.

Molecular Epidemiology of Ticks and Tick-Borne Pathogens in the Ta-Pa Mountain Area of Chongqing, China

To validate the prevalence and biodiversity of ticks and tick-borne pathogens in Chongqing, a total of 601 ticks were collected from dogs, cattle, and goats within the Ta-pa Mountain range in Chongqing, China. Five distinct tick species were identified, including Ixodes ovatus (1.66%, 10/601), I. acutitarsus (0.50%, 3/601), Haemaphysalis flava (10.32%, 62/601), Ha. hystricis (9.82%, 59/601), and Ha. longicornis (77.70%, 467/601). A suit of semi-nest PCR and nest PCR primers were custom-synthesized for the detection of tick-borne pathogens. The analysis yielded positive results for 7.15% Rickettsia (Candidatus R. principis, R. japonica, and R. raoultii), 3.49% Anaplasma (A. bovis and A. capra), 1.16% Ehrlichia, 1.83% Coxiella burnetii, and 3.49% protozoa (Theileria. capreoli, T. orientalis, T. luwenshuni, and Babesia sp.) in ticks. Notably, Ca. R. principis was identified for the first time in I. ovatus and Ha. longicornis. These findings underscore the significant prevalence and diversity of ticks and their associated pathogens within the Chongqing Ta-pa Mountain region. This study accordingly provides an extensive dataset that contributes to the epidemiological understanding and disease prevention strategies for tick-borne illnesses in the local area.

At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)

Abstract. This paper introduces the AtsMOS (At-scale Model Output Statistics) workflow, designed to enhance mountain meteorology predictions through the downscaling of coarse numerical weather predictions using local observational data. AtsMOS provides a modular, open-source toolkit for local and large-scale forecasting of various meteorological variables through modified model output statistics – and may be applied to data from a single station or an entire network. We demonstrate its effectiveness through an example application at the summit of Mt. Everest, where it improves the prediction of both meteorological variables (e.g. wind speed, temperature) and derivative variables (e.g. facial frostbite time) critical for mountaineering safety. As a bridge between numerical weather prediction models and ground observations, AtsMOS contributes to hazard mitigation, water resource management, and other weather-dependent issues in mountainous regions and beyond.

Assessment of dynamic responses and impact resistance of corrugated plate-reinforced concrete tunnels under irregular rockfall scenarios.

This article presents a composite tunnel rockfall protection structure (CPRC) employing galvanized corrugated steel plates as the inner formwork for reinforced concrete structures. It addresses the threats posed by frequent rockfall disasters in mountainous regions with complex geology. The research investigates impact damage from various rockfall shapes through numerical simulations and experiments on five representative forms, comparing traditional reinforced concrete structures RC with CPRC. The study highlights both structures' dynamic responses and damage characteristics across different impact scenarios, introducing the Residual Resistance Index RRI as a measure of post-impact safety performance. Results show that the numerical simulations align with laboratory tests, with discrepancies within 10%, validating the simulation method's accuracy in predicting impact resistance. Following impacts, both structures primarily displayed brittle concrete damage; however, the CPRC structure demonstrated a 79.46% reduction in concrete damage and an 86.31% decrease in reinforcement damage. The energy-dissipating properties of the corrugated plates significantly lowered rockfall penetration depth and impact energy transfer ratio, with an RRI exceeding 0.88 post-event. Additionally, the study reveals varying damage effects from different rockfall shapes, further supporting the CPRC structure's superior impact resistance and its effectiveness in preventing secondary disasters in tunnel engineering within mountainous terrains.

The rise and transformation of Bronze Age pastoralists in the Caucasus.

The Caucasus and surrounding areas, with their rich metal resources, became a crucible of the Bronze Age1 and the birthplace of the earliest steppe pastoralist societies2. Yet, despite this region having a large influence on the subsequent development of Europe and Asia, questions remain regarding its hunter-gatherer past and its formation of expansionist mobile steppe societies3-5. Here we present new genome-wide data for 131 individuals from 38 archaeological sites spanning 6,000 years. We find a strong genetic differentiation between populations north and south of the Caucasus mountains during the Mesolithic, with Eastern hunter-gatherer ancestry4,6 in the north, and a distinct Caucasus hunter-gatherer ancestry7 with increasing East Anatolian farmer admixture in the south. During the subsequent Eneolithic period, we observe the formation of the characteristic West Eurasian steppe ancestry and heightened interaction between the mountain and steppe regions, facilitated by technological developments of the Maykop cultural complex8. By contrast, the peak of pastoralist activities and territorial expansions during the Early and Middle Bronze Age is characterized by long-term genetic stability. The Late Bronze Age marks another period of gene flow from multiple distinct sources that coincides with a decline of steppe cultures, followed by a transformation and absorption of the steppe ancestry into highland populations.

The Pyrenean Platform for Observation of the Atmosphere: site, long-term dataset, and science

Abstract. The Pyrenean Platform for Observation of the Atmosphere (P2OA) is a coupled plain–mountain instrumented platform in southwestern France. It is composed of two physical sites: the “Pic du Midi” mountaintop observatory (2877 m a.s.l.) and the “Centre de Recherches Atmosphériques” (600 m a.s.l). Both sites are complementarily instrumented for the monitoring of climate-relevant variables and the study of meteorological processes in a mountainous region. The scientific topics covered by P2OA include surface–atmosphere interactions in heterogeneous landscapes and complex terrain, the physics and chemistry of atmospheric trace species at a large scale, the influence of local- and regional-scale emissions and transport on the atmospheric composition, and transient luminous events above thunderstorms. With a large number of instruments and a high hosting capacity, P2OA contributes to atmospheric sciences through (i) building long-term series of atmospheric observations, (ii) hosting experimental field campaigns and instrumental tests, and (iii) educational training in atmospheric observation techniques. In this context, P2OA is part of the French component of the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS-Fr) and also contributes to the Integrated Carbon Observation System (ICOS) research infrastructure and to several European or international networks. Here, we present the complete instrumentation of P2OA and the associated datasets, give a meteorological characterization of the platform, and illustrate the potential of P2OA and its dataset with past or ongoing studies and projects.