XTREES – Xylem Traits and Extreme EventS (Marco Carrer, marco.carrer@unipd.it)

Extreme weather events (e.g., windstorms, late frosts) can produce significant impacts on forest ecosystems. However, when such events do not result in visible disturbances (e.g., treefall or defoliation), detecting their effects on tree vegetation becomes particularly challenging. This is primarily due to the long lifespan and resistance of trees, which enables them to withstand even intense but short-lived climatic phenomena without exhibiting evident damage.
The aim of this project is to identify and analyze the effects of extreme climatic events that are not always associated with visible canopy-level disturbances. By conducting detailed anatomical analyses of xylem traits—such as vessel and tracheid size and distribution, as well as the presence of traumatic tissues or parenchyma components—the project will attempt to detect permanent imprints of flash droughts, cold and heat waves, and windstorms.
The study will focus on the most widespread broadleaf and conifer species in Europe, including beech, Norway spruce, silver fir, Scots pine, oaks (Quercus spp.) and a shrub, common juniper. Collaborating with climatologist Michele Brunetti (CNR), the project will utilize long daily climate records, spanning at least a century, to extract extreme events and correlate them with long-term time series of xylem anatomical trait. In parallel, satellite data analysis—conducted in collaboration with Francesco Pirotti—will be used to upscale the effects of these climatic events and verify their correspondence with vegetation signals over the past two to three decades. These combined approaches will facilitate a spatiotemporal calibration between extreme events, such as flash droughts, and their anatomical imprints.
Ultimately, this research could enable the reconstruction of these relatively elusive climatic phenomena on multi-century timescales, allowing for a better contextualization of their current intensity and frequency within a long-term perspective.

  Climatic response of the alpine cryosphere and related impacts on water resources, slope instability and environmental conditions (Luca Carturan, luca.carturan@unipd.it)

Many mountain chains in the world, including the Alps, are characterised by the presence of perennial elements of the alpine cryosphere, such as glaciers and permafrost, as well as transitory components such as the seasonal snowpack. Many of these mountain ranges are experiencing the warmest temperatures since deglaciation, and the warming rate is accelerating, leading to fast degradation of the mountain cryosphere.
If on one hand individual processes of cryosphere degradation are fairly well known, the full response of the alpine cryosphere depends on a chain of interrelated processes whose cascading effects on water resources, slope instability and environmental conditions are still poorly investigated. As demonstrated by recent high-magnitude events in the Alps, it is no longer possible to consider the single components of the alpine cryosphere in isolation to explain how the cryospheric system is changing.
During this PhD, we propose an interdisciplinary study of how the alpine cryosphere in the Eastern Italian Alps is responding to the accelerated atmospheric warming. Based on long-term collections of field data and ongoing monitoring activities, we propose: i) to analyse historical trends and seasonal variations in permafrost- and glacier-related variables, ii) to enhance existing glacier and permafrost monitoring networks, iii) to analyse interdisciplinarily recent ground instabilities triggered by cryosphere degradation, and iv) to outline possible future impacts on water resources, slope instability and ecosystems.
Activities will include the joint analysis and modelling of long datasets regarding, among others, ground surface temperature, permafrost temperature, rock glacier activity, spring water temperature, glacier mass balance, and climatological and nivo-meteorological data series.
The results of the PhD project will have significant impacts on the knowledge and projection of climate related transformations in the alpine cryosphere, and of related cascading effects on water resources, slope instability and ecosystems.

  Forest carbon dynamics under climate change: bridging dendrochronology and ecosystem flux measurements (daniele.castagneri@unipd.it)

Forests play a critical role in the global carbon cycle, yet the mechanisms linking climate variability to primary productivity and woody biomass growth remain poorly understood (Cabon et al., 2022). This PhD project aims to advance our knowledge of these complex interactions by integrating dendrochronology and Quantitative Wood Anatomy (QWA) with carbon flux estimates derived from both direct observations and remote sensing data.
The core methodological approach combines tree-ring width analysis and QWA (von Arx et al., 2017) with eddy covariance flux measurements and satellite-derived productivity estimates (Rita et al., 2020). This multi-proxy framework will allow investigation of the temporal coupling and decoupling between carbon uptake and woody biomass formation. Investigations will mostly focus on pure conifer (Picea spp. and Pinus spp.) stands allowing using QWA to assess woody biomass growth variations, from intra-annual to decadal scales (Puchi et al., 2023; 2024). Different forest ecosystems will be investigated, from boreal and temperate to Mediterranean and semi-arid forests.
The main research objectives include: (i) identifying climate drivers of carbon flux variability; (ii) assessing intra- and inter-annual woody biomass growth dynamics through innovative anatomical proxies; (iii) integrating remote data to direct observations and measurements; (iv) provide mechanistic insights into climate influence on the temporal coupling between carbon uptake and woody biomass formation in forest ecosystems.
The PhD programme will have a strongly interdisciplinary character, supported by collaborations with national and international experts in forest ecology, wood anatomy, ecosystem monitoring, and remote sensing. Planned periods abroad include leading research institutions such as the Universitat Autònoma de Barcelona, Faculty of Biology, or the Consejo Superior de Investigaciones Científicas (CSIC), both recognized for their excellence in forest carbon cycle research. This interdisciplinary training will equip the doctoral candidate with a broad expertise across key research domains — including forest ecology, carbon cycling, dendrochronology, and climate science.

  Debris flow triggering, development and impacts on the upper zones of mountain catchments (Vincenzo.dagostino@unipd.it)

Research on debris flows and highly concentrated torrential flows has traditionally more focused on catchments where such processes reach valley bottoms because the presence of settlements implies a high damage potential. However, as a consequence of climate change, an increasing frequency and intensity of events is being observed in headwater catchments, where debris flows often initiate and dissipate without propagating to downstream populated areas. In these environments, which remain underrepresented in both scientific literature and risk management practices, several exposed elements are present, including alpine huts, pastures, ski infrastructures, water intakes, reservoirs, as well as dense networks of forest roads and hiking trails. These infrastructures, in addition to the fact that they represent exposed elements, may actively influence geomorphological processes by altering hillslope hydrology, sediment connectivity, and, in some cases, contributing to the initiation or modification of debris-flow propagation.
Despite the growing body of research on the effects of linear infrastructures on hydro-geomorphological processes, existing risk assessment methodologies have been primarily developed for major transportation networks and are not readily transferable to high-mountain environments. These settings are characterized by lightweight infrastructures, possible human presence, and specific environmental constraints. In particular, integrated approaches capable of quantitatively or semi-quantitatively assessing the risk associated with the interaction between debris flows and forest roads or trail systems are still lacking.
This PhD experimental project aims to address this gap by developing an integrated framework for process understanding and risk assessment in headwater catchments. The specific objectives are:

• to quantitatively improve knowledge on debris-flow initiation, propagation, and deposition in the upper zones of mountain catchments;
• to investigate the role of forest roads and trails in modifying soil and land instabilities at the hillslope–channel interface;
• to assess the exposure and vulnerability of lightweight infrastructures to debris-flow processes;
• to define an operational framework to support the design of protection measures, the management and the adaptation of forestry roads and trails with a particular focus on the upper zones of mountain catchments exposed to debris-flow hazard.

The methodology will be structured into multiple phases. In the first phase, a pilot catchment in the Eastern Dolomites (Rio Gardeccia-Soial, Val di Fassa, Italy), recently instrumented with rain gauges, flow level sensors, and video monitoring systems, will be analysed. Multi-temporal orthophotos and LiDAR data will be integrated with in situ measurements collected over three monitoring seasons (June–October), enabling the reconstruction of events and the quantification of key morphodynamic indicators.
In a second phase, a set of comparable catchments will be selected, characterized by different configurations of forest road and trail networks and varying levels of interaction with debris-flow processes. This comparative analysis will enable the identification of common controlling factors and the assessment of the role of infrastructures in modulating process dynamics. The results will also support the evaluation of adaptation strategies for forest roads and trail networks, not only in terms of protective measures, but also by exploring alternative alignments and spatial planning solutions aimed at locating them in less hazard-prone areas and thereby reducing overall risk.
Building on the experience gained from field monitoring activities (Rio Gardeccia) and the analysis of selected case studies, the research will contribute to the development of an operational framework integrating approaches for process prediction and impact assessment with tailored strategies for planning, design, and management of anthropogenic elements (e.g. forest roads, access routes, and recreational uses). The framework will aim to support the mitigation of risk, including its residual component, associated with debris-flow processes in high-mountain environments.

  Sponge City-Oriented Green Planning (Catherine Dezio, catherine.dezio@unipd.it)

This PhD research investigates how sponge city principles can be implemented within already urbanized landscapes, where spatial, regulatory, and physical constraints significantly limit the scope of intervention. In these contexts, the challenge lies not in designing new green systems, but in the retrofitting and reconfiguration of existing urban fabrics. The grant proposal focuses on how green infrastructure systems—such as urban forests, parks, water retention areas, and peri-urban agricultural spaces—can be strategically mobilized to improve water retention, infiltration, and ecosystem services in Italian foothill and lowland cities. The so-called “Sponge City” paradigm frames urban landscape planning as a strategy to address climate change adaptation, urban flooding, and environmental inequalities.
The research aims to:

1. analyze the spatial and ecological potential of urban and peri-urban green spaces to function as water-sensitive infrastructures;
2. develop regenerative planning strategies that integrate hydrological performance and water quality objectives;
3. propose policy and planning tools that integrate sponge city principles into urban and regional planning frameworks.

The study is situated at the intersection of landscape planning, climate adaptation, and ecological urbanism, engaging with the growing international debate on nature-based solutions and water-sensitive urban design. Particular attention will be paid to the role of green infrastructure in addressing environmental justice, exploring how climate adaptation strategies can also improve access to ecosystem services and urban livelihoods for underserved populations.
Methodologically, the research will combine quantitative and qualitative approaches, including literature review, multi-scalar spatial analysis, GIS-based mapping of ecosystem services and hydrological dynamics, and design-oriented research. The work will include the analysis of selected case studies, the identification of retrofit strategies, and the development of planning scenarios. Fieldwork observations and stakeholder engagement (i.e. living labs, interviews) will support the interpretation of local constraints and opportunities. The approach integrates existing green planning standards (e.g. 3-30-300, 15-minute city, Italian ministerial standards) with recent international experimental research on emerging metrics for green infrastructure, extending them to incorporate water-related dynamics—considered not only in terms of risk mitigation, but also in relation to the provision of broader ecosystem services and their contribution to urban accessibility and use.
The expected outcome is a critical assessment of barriers and enabling conditions for the transition towards sponge cities, together with an integrated framework aligning sponge city principles with green planning practices, and a set of policy-oriented integrated recommendations for more resilient, inclusive, and ecologically functional urban landscapes.

  Prediction of avulsions and the extent of routed areas on debris-flow fans and cones (Carlo Gregoretti, carlo.gregoretti@unipd.it)

Debris flows (DFs) are solid–liquid currents that propagate along channels and slopes and are generated by the impact of abundant runoff on debris deposits. During propagation, DFs volumetrically grow through sediment entrainment, proportionally to the triggering runoff volume, reaching volumes up to ten times larger (Simoni et al., 2020). Extreme rainfall events that produce abundant runoff (Bollschweiler and Stoffel, 2010), as well as rock failures that, together with permafrost degradation, increase sediment availability (Damm and Felderer, 2013; Stoffel et al., 2014; Rengers et al., 2020), are becoming more frequent. Consequently, both the frequency and the magnitude of DFs are increasing.
The growing occurrence of DF events transporting large sediment volumes highlights the need for hazard assessment and effective countermeasures. DF hazard assessment largely relies on identifying areas potentially affected by these processes. In this context, the study of debris-flow avulsion (De Haas et al., 2018) is crucial for both hazard assessment and the planning of mitigation measures.
This doctoral project aims to identify the geological and geomorphological conditions that control avulsion processes and to determine the resulting post-avulsion flow paths. The first step will investigate the relationships between avulsion locations and channel characteristics, identify the control-ling factors, estimate the probability of avulsion at specific locations, and develop a method to predict avulsion points. The second step will calibrate and validate the probabilistic mapping procedure for debris-flow paths on alluvial fans proposed by Schiavo et al. (2024). The final step will couple the identification of avulsion points with the validated procedure of Schiavo et al. (2024) to deter-mine flow directions after avulsion, and, therefore the extent of the area threatened by DFs.
Identifying avulsion points and subsequent flow paths is essential for debris-flow hazard assessment on alluvial fans and for designing effective countermeasures in a changing climate.

  From tree to landscape: understanding Old Growth Forest structure and dynamics with a multi-level approach (Emanuele Lingua, emanuele.lingua@unipd.it )

Old-growth forests (OGF) represent some of the most ecologically valuable ecosystems on Earth, hosting exceptional biodiversity and playing a crucial role in carbon storage and ecosystem stability. Despite their ecological importance, OGFs still lack standardized structural indicators, which significantly limits their identification and mapping at large scales (Hirschmugl et al. 2023).
This research aims to characterize the vertical and horizontal structure of OGF and second-growth forests in the Italian Alps, using an integrated geomatics approach combining ground-based surveys and remote sensing data, particularly LiDAR and multispectral imagery. Tree spatial pattern analysis will be employed as a key descriptor of forest dynamics resulting in structural complexity (Petritan et al. 2014). The high-resolution dataset obtained from surveying will also be used to identify the most informative yet cost-effective indicators that can be determined from large-scale remote sensing data to define an effective model for OGF detection applicable at broader spatial scales (Adiningrat et al. 2024, Hevia et al. 2022).
To ensure ecological transferability, the structural indicators developed in the Alpine context will be compared with those from forest ecosystems in other geographical regions, testing the robustness and generalizability of the proposed approach across different environmental conditions.
The expected outcomes include a set of validated remote sensing-based structural indicators for OGF identification, and a scalable detection framework applicable to identify other OGFs and forest monitoring and conservation planning. As highlighted by Hirschmugl et al. (2023) and Adiningrat et al. (2024), combining 3D structural data with multispectral information significantly improves classification accuracy, supporting the methodological choices of this proposal.

  Territories in Transition: LAGs, Rural Tourism, and the Geography of Tourism Redistribution (Francesco Pagliacci, francesco.pagliacci@unipd.it )

This PhD proposal examines the potential of rural tourism to mitigate overtourism. Currently, overtourism is a critical issue in major Italian destinations, generating environmental, social, and economic pressures. In contrast, rural and peripheral areas—often rich in landscape, cultural, and agri-food assets—remain marginal to tourism flows and underutilize their development potential. This research investigates which territorial characteristics can attract alternative tourism demand and contribute to a more balanced spatial distribution of flows.
The project focuses on the role of LEADER programmes and Local Action Groups (LAGs) as key actors in place-based rural development. Through integrated governance approaches, LAGs can strengthen local value chains, foster tourism diversification towards more sustainable forms, and enhance territorial identity and attractiveness. LAG-based systems are thus considered a central analytical lens to assess the capacity of rural tourism to rebalance tourism dynamics.
The main objectives are: (i) mapping tourism flows and identify spatial hotspots; (ii) analyzing interactions between tourism intensity and distribution of rural tourism assets and LAG-supported territories; (iii) evaluating whether LAG-based rural economies act as territorial anchors capable of redistributing demand and alleviating pressure on saturated destinations; and (iv) providing policy recommendations for strengthening rural tourism through integrated strategies.
Methodologically, the project combines GIS-based spatial analysis (e.g., Moran’s I), accessibility and spatial interaction models, and econometric techniques (including panel data and spatial econometrics). These approaches are complemented by Social Network Analysis (SNA), aimed at reconstructing and analysing origin–destination tourism flows across municipalities. By modelling tourism as a network of interconnected places, the project will identify central and peripheral nodes, patterns of concentration and dispersion, and the role of rural territories within the broader tourism system. Where direct origin–destination matrices are not fully available, the analysis will rely on data integration and estimation techniques to approximate inter-territorial flows.
These quantitative methods are complemented by primary data collection through surveys and interviews with tourists, rural operators, and LAG stakeholders, as well as comparative case studies of selected territories.
By integrating spatial, econometric, and network-based approaches in a multidisciplinary perspective, the project aims to generate a more comprehensive understanding of tourism dynamics and their territorial impacts. Importantly, the inclusion of SNA enables the identification of structural imbalances in tourism flows and the detection of potential redistribution pathways toward rural areas.
Expected outcomes go beyond academic contributions. The project will provide evidence-based policy indications and develop decision support tools to assist local policymakers, destination managers, and LAGs in more effectively managing tourism flows. These tools will support the design of place-based strategies aimed at reducing pressure on saturated destinations, enhancing the attractiveness of rural areas, and promoting a more balanced and sustainable tourism system.

  Drivers of International Demand for Prosecco: A Trade Economics and Econometric Approach (Luca Rossetto, luca.rossetto@unipd.it )

The proposed research project is linked to an upcoming research initiative on the Prosecco supply chain, a product strongly oriented toward international markets. The main objective is to analyse how trade policies and socio-economic conditions in importing countries influence export performance and consumption patterns of Prosecco.
From a scientific perspective, the project builds on the literature on agri-food trade and demand analysis. Previous studies on sparkling wines show that consumption is highly sensitive to income and price dynamics, highlighting the income-elastic nature of these products and the heterogeneity of demand across markets. At the same time, empirical evidence on Prosecco trade, in line with the trade economics theory, indicates that export flows are significantly influenced by macroeconomic variables, such as GDP in importing countries, as well as by trade barriers including tariffs and regulatory constraints. Within a highly competitive and globalised wine market, these elements suggest that the positioning of Prosecco may be particularly exposed to changes in economic conditions and trade policies.
Methodologically, the research will be structured along two complementary levels. First, a trade economics approach will be adopted to assess the impact of tariffs, non-tariff barriers and institutional frameworks on export performance. Second, the project will develop an econometric model of demand and supply aimed at capturing the relationship between Prosecco consumption and the identified economic variables. The model will be used to simulate alternative scenarios related to potential policy changes and macroeconomic shocks.
The expected outcome is to provide a deeper understanding of the determinants of international demand for Prosecco and to support policy and strategic decision-making in export-oriented agri-food systems.

  Optimizing Agricultural Machinery with AI for Sustainable Plant Management (Luigi Sartori, luigi.sartori@unipd.it)

The recently published document on the Strategic Dialogue on the Future of EU Agriculture (December 2024) highlight the importance of reducing plant protection products (PPPs) while developing and utilizing biocontrol. These practices may involve the use of innovative and sustainable technologies, such as more efficient spraying machinery, and AI-driven spraying technologies. This research proposes an integrated approach utilizing artificial intelligence (AI), on-machine disease detection, precision and automation in spraying, addressing the need for more efficient pest and disease management.
The study aims to develop two interconnected AI-driven systems:
1-AI-driven plant features detection on farm machinery:
This system uses high-performance computing and deep learning for real-time features recognition (disease symptoms, plant structural features). Edge computing enables immediate identification, allowing for timely intervention. Models will be trained on field-acquired agricultural datasets, and field trials will measure this technology’s effectiveness compared to traditional inspection methods, focusing on detection accuracy and operational speed.
2- Precision and automation in PPP application system:
This component proposes to equip unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and conventional sprayers with the aforementioned AI technology for on-the-go disease detection and canopy volume assessment. Monocular Depth Estimation (MDE) or analogous AI-driven depth perception methodologies might be used to estimate key canopy metrics, including Leaf Area Index, Tree Row Volume, and Leaf Wall Area. These AI-derived metrics inform a UAV/UGV/conventional sprayer system employing Pulse Width Modulation nozzles. The selected UAV/UGV/conventional sprayer might be tested with state-of-the-art equipment for droplet analysis, drift measurement, 3D anemometer, vertical bench testing, and spray pattern assessment.
This project expects to demonstrate how AI-enhanced farm machinery can lead to substantial reductions in PPP usage, lower environmental footprint, and improved crop health and yield.

Statement: we agree to reserve 5.000 Euros to support the payment of the compulsory health insurance (for foreign candidates) and 6 months abroad period of any PhD candidate who will be selected.

  Economic Valuation of Green Care Ecosystem Services (Laura Secco, laura.secco@unipd.it )

PhD research proposals should address a key research gap within the framework of the EU bioeconomy, namely the limited economic valuation of cultural ecosystem services (CES) associated with “green care initiatives” (GCI), with emphasis on forest-based initiatives.
On the one hand, the benefits to humans deriving from GCI can and should be conceptualized as a distinct category of ecosystem services directly connected and aimed to human health. Despite growing importance, forest-based health benefits remain overlooked in economic terms. This limits their recognition in bioeconomy, public health policies, and investments. While GCI generate measurable health outcomes, the lack of specific, robust economic valuation and the limited integration of CES into EU bio-economy frameworks lead to incomplete cost-benefit analyses, which ultimately results in weak support for both sectoral and cross-sectoral policy development and effective regional strategies. Emerging green jobs that uptake GCI, potentially offering income increase and diversification in rural and urban areas, are not yet clearly regulated, and their economic contribution to the forest-based bioeconomy remains largely unknown.
On the other hand, GCI can transform the way how people look at forests, increasing pro-environmental behaviour and changing human’s attitude towards nature, shifting from a currently dominant instrumental to a relational value, having several policy implications.
Proposed research approaches include (are not limited to): systematic literature review; design and implementation of individual/collective questionnaires/interviews and methods for economic evaluation of health benefits and trade-offs with other ecosystem services. The use of advanced analytical tools, including AI, to support cost/benefit analyses, explore human/nature relations, and develop policy-relevant assessment frameworks to estimate green care’s societal-economic value and inform EU policies are expected. Interdisciplinary collaboration (e.g. psychology, medicine, ecology) is encouraged. Expected outputs include robust estimates of the economic value of GCI-related forest ecosystem services, updated insights on human-nature relations, evidence-based policy recommendations. PhD research proposals should foresee a 6-months mobility period abroad.

  Climate and market risk modelling for agricultural income stabilization at farm and collective levels (Samuele Trestini, samuele.trestini@unipd.it )

The project is grounded in the literature on agricultural risk management and climate change economics, which highlights the increasing exposure of agricultural income to climate variability and extreme events (EIB, 2025). International organizations have emphasized the need for more forward-looking and integrated approaches to risk management that combine farm-level strategies with systemic instruments. In parallel, recent developments in the reform of the Common Agricultural Policy (CAP) have strengthened the role of risk management tools and opened new perspectives for crisis management instruments and funds targeting extreme events (World Bank, 2026).
In this context, particular attention is given to the role of collective risk management mechanisms not only in stabilizing farm income (World Bank, 2016), but also in enhancing the resilience of agri-food systems and contributing to food security. By pooling risks across farms and regions, collective instruments can mitigate systemic shocks, reduce income volatility at aggregate level, and support continuity of production under adverse climatic conditions.
The research project aims to develop economic risk models integrating climate scenarios to assess and manage income variability in agricultural systems, considering both individual farm performance and collective risk management schemes such as mutual funds and insurance mechanisms.
The specific objectives of the research are: (i) to analyse the relationship between climate variability and farm income dynamics; (ii) to develop scenario-based economic models to assess future income risks under alternative climate conditions; and (iii) to evaluate the role of different risk management tools, including insurance schemes, mutual funds, and emerging crisis management instruments within the CAP framework.
The methodological approach will combine economic modelling with climate scenarios and farm-level data.
Particular attention will be given to the interaction between individual behaviour and collective risk-sharing mechanisms within evolving policy frameworks.
The expected outcomes include improved understanding of climate-driven income risks and policy-relevant insights to support the design of more resilient agricultural systems, with benefits for both farm income stabilization.

  Study, selection and winemaking of new crossings produced from vine varieties resistant to major fungal diseases (downy mildew and powdery mildew) aimed to reduce the use of fungicides and improve sustainability and adaptability to climate change in wine

PREMISE
Many valuable V. vinifera varieties are susceptible to the main fungal diseases of the grapevine (downy mildew and powdery mildew) and require numerous annual pesticide treatments in unfavorable years. CREA-VE is currently conducting a genetic improvement program to produce new valuable varieties tolerant to these diseases (e.g., Glera, Raboso) through crossbreeding with resistant hybrid grape varieties. Molecular marker-assisted selection (MAS) allows for the selection of seedlings with multiple resistance genes, which are grown in experimental vineyards for morphological and agronomic evaluation.
ACTIVITIES
In this project, the grapes and wines from the most promising selections will be subjected to in-depth chemical and organoleptic investigations to characterize the metabolites present in the berry and determine the organoleptic characteristics of the experimental wines that will be produced.
Through metabolomics studies, using gas chromatography/mass spectrometry (GC/MS) methods, the aromatic profiles of grapes harvested over multiple years, and their resulting wines will be characterized. Using ultrahigh-resolution mass spectrometry (UHPLC/QTOF) techniques, glycosylated aromatic precursors and other classes of polar metabolites that determine the chemical, oenological, organoleptic, and nutraceutical properties of the products (flavonols and flavanonols, flavan-3-ols and proanthocyanidins, phytoalexins and stilbene compounds, etc.) will be studied.
The complete chemical-analytical investigation of the samples, at the end of the research, will allow to select the resistant genotypes producing grapes with the chemical-organoleptic characteristics most suitable for the production of high-quality wines.
WORKPLACE
CREA-VE Conegliano
CIRVE Conegliano

  Soil Erosion Dynamics in Complex Agricultural Landscapes: Multi-Scale Monitoring and Climate-Resilient Mitigation Strategies (Giulia Zuecco, giulia.zuecco@unipd.it)

Soil erosion represents a major threat to agricultural practises and crop productivity. At the global scale, about 2.8 tonnes of soil are lost per hectare every year (JRC), with critical impacts on land degradation and soil ecosystem services, including food provisioning, nutrient cycling and water purification (Baartman et al., 2022; Lal, 2014). In agricultural areas, erosion is often intensified by poor land‑use practices, leading to an ecological imbalance in surrounding ecosystems. Monitoring erosion processes and their driving factors is, therefore, crucial for understanding spatial dynamics and guiding conservation strategies. Recent advancements in remote sensing have greatly improved large‑scale erosion assessment, enabling accurate detection of erosion patterns and factors influencing soil loss (Ikram et al., 2025). Predictive models—ranging from machine‑learning–based susceptibility mapping to established approaches such as USLE and RUSLE—provide valuable tools for estimating future erosion risks and supporting informed decision‑making for sustainable land management. Nonetheless, integrated approaches combining remote sensing, hydrometeorological data and process-based models able to predict water erosion and sediment fluxes are rarely used. The implementation of such approaches could enhance early‑warning measures and help identify high‑risk agricultural zones, ultimately contributing to long‑term soil conservation planning.
Given the above background, this proposal is aimed at i) investigating soil erosion dynamics and their key drivers in different agricultural landscapes, ii) predicting soil loss under future climate scenarios, and iii) providing recommendations to farmers for a better soil and water conservation.
Research activities will be conducted within the EUROSION project (Horizon EU) framework and in collaboration with Consorzio di Bonifica di II grado Lessinio Euganeo Berico. Erosion and hydrometeorological observations and modelling applications will be conducted at the Italian Monitoring Node, consisting of three study sites covered with different crops and under different management practises.

  GeoAI4ES – Artificial Intelligence for Environmental Monitoring and Ecosystem Services Mapping (Francesco Pirotti, Francesco.pirotti@unipd.it )

The research project aims to develop advanced algorithms for the processing and analysis of satellite imagery, with the goal of producing dynamic and highly accurate maps of environmental variables. These estimates will be integrated into the assessment of related ecosystem services.
The initiative is positioned within a rapidly evolving international landscape, characterized by numerous programs focused both on the development of intelligent platforms for environmental monitoring and on the modeling of ecosystem services.
In this context, the evolution of decision support systems, together with the growing adoption of artificial intelligence, opens new opportunities to enhance the extraction of information from complex data. In particular, the project proposes the use of hybrid approaches that combine advanced statistical methods with geospatial information. The underlying research hypothesis is that such integration can significantly improve the effectiveness of analyzing complex environmental phenomena and predicting future scenarios, with important implications for both scientific research and practical applications.

  Multi-modal data fusion for accurate detection of forest parameters (Francesco Pirotti francesco.pirotti@unipd.it)

Multi-modal surveying involves the integration of spatial and environmental data acquired through diverse methods and technologies. By leveraging complementary sensors, platforms, and processing techniques, multi-modal data can significantly enhance accuracy, coverage, and efficiency.
This PhD project, financed by FBK - Fondazione Bruno Kessler, will see the candidate work in Trento with the 3DOM research unit of FBK focusing on investigating optimal methods for collecting, processing, and fusing spatial data in forest environments.
The research will encompass, but is not limited to, photogrammetry, laser scanning (mobile, static, aerial, drone, and terrestrial), optical multi-/hyperspectral, and radar remote sensing. Forest environments present unique challenges due to complex geometric structures, accessibility constraints, heterogeneous canopies, dynamic elements, and occlusions. The project aims to demonstrate that processing and fusion techniques—including AI-based approaches—applied to multi-modal datasets can advance the state of the art in mapping, enabling improved identification of tree species, spatial distribution, forest structures, and ecological variables over time.
The candidate should have a problem-solving mindset in programming environments and a strong foundation in spatial data management and analysis. Ideal backgrounds include computer science, engineering, or natural/environmental/forestry sciences, with a strong predisposition to apply computer science skills to the programming and processing of 3D spatial data, including point clouds and multi-source geospatial datasets.

  Agriculture, forest and food economics and policy

1. Economics and policy for resilient agriculture and forest management.
   Agricultural and forest economics and policy need to be innovated, for more resilient societies in Europe and worldwide. Particular attention is given to the Common Agricultural Policy analysis and other sectoral policies, impact assessments on farms and forest managers' economics, organization and resilience, rural development, market functioning, organic farming, innovative forest management, agri-environmental measures adoption, and risk management strategies and tools. (Rossetto, Trestini, Pagliacci, Cei, Giampietri, Masiero, Gatto, Pisani, Secco).
   
   
2. The food and the agri-food world.
   Competitiveness and innovation of food products and agri-food chains are crucial to promote food products on global markets. Relevant topics of interest in this research field are: consumers' behaviour towards food quality attributes related to environmental sustainability and production methods (e.g. organic farming), new food products, nutrition and health-related issues, as well as alternative food networks and policy and labelling tools such as food claims, Geographical Indications, property rights protection. (Rossetto, Pomarici, Trestini, Pagliacci, Giampietri, Thiene, Franceschinis, Vecchiato, Cei).
   
   
3. The wine market in Italy and worldwide: a sustainability perspective.
   Assessing market dynamics and the impact of sectoral policies on wine economics is crucial to support this relevant sector. International market analysis and the impact of national regulations, taxation, and trade agreement on wine market, as well as organizational factors affecting wine supply chain performance, including quality and quantity policy adopted by producers’ organizations, need to be understood. Factors related to the adoption of more sustainable (environmental and social) solutions and market opportunities for more sustainable grape and wine production need to be identified (Pomarici, Galletto, Rossetto, Trestini, Giampietri).
   
   
4. Advanced methods for land and real estate valuation.
   Innovative methods for the analysis of land and real estate values such as Standard Hedonic Pricing Models, Spatial Autoregressive Models, Quantile Regression, Machine Learning and Big Data analysis have to be developed, tested and applied to deepen the scientific knowledge on their implications and their interactions with environmental quality and environmental policies. (Thiene, Vecchiato, Franceschinis).
   
   
5. Valuing natural resources for more informed decision-making towards sustainability.
   Economic valuation of natural resources, non-market goods, and ecosystem services is functional to provide crucial information to support decisions of both public and private actors. Special attention is given to the demand of nature-based tourist-recreational and cultural ecosystem services, as well as forest-based regulating services considering environmental and social sustainability. (Thiene, Vecchiato, Franceschinis, Gatto, Secco, Masiero, Pisani).
   
   
6. Innovations for a forest-based bioeconomy.
   Forests are expected to have a growing role in the bioeconomy at national and global levels. Relevant topics of research interest are related to analysing at the global and local scales the policy framework, market trends, social and environmental responsibility associated with the development of a forest-based bioeconomy, with a focus on innovative wood products (e.g., engineered wood products, man-made cellulose fibers, bioplastics etc.) as well as non-wood (i.e., wild) products and services. (Masiero, Gatto).
   
   
7. Transformative processes and Green Transition in Forests and the Environment.
   The current socio-economic and environmental crises call for an urgent reconceptualization of the relations between natural and institutional-social-human capitals, with special attention to forest resources. Research can contribute through multi-level policy evaluation and governance analysis in urban, peri-urban and rural areas, with a focus on policy instruments coordination, innovative entrepreneurial tools and activities, property rights and other legal- and institutional-related issues. (Gatto, Secco, Pisani, Pagliacci, Masiero).

  Forest ecology and forest management

1. Forest dynamics and natural disturbance ecology.
   Analysis of forest stands development, assessment and modelling of mortality processes, facilitation and competition mechanisms, and regeneration dynamics in a context of climate change. Old growth forest characterization and identification. Allometric approaches for assessing the degree of disturbance in different forests. Analyses and modelling of natural disturbances impacts in forest ecosystems and post-disturbance dynamics. Soil biodiversity and ecosystem services. (T. Anfodillo, M. Carrer, E. Lingua, G.Petit).
   
   
2. Forest management.
   In a context of global change, implementation of sustainable forest management strategies, adaptive management and  agro-forestry systems for biomass and quality timber production. Management of protected area, forest biodiversity conservation and management both inside and outside Natura 2000 ecological network. Implementing and monitoring silvicultural interventions for natural disturbance prevention and impact mitigation. (T. Anfodillo, E. Lingua, T. Sitzia).
   
   
3. Forest ecology and ecophysiology.
   Plants responses to abiotic and biotic stress analysed using physiological measurements (e.g., sapflow, leaf gas exchange, xylem vulnerability to air embolism), quantitative xylem and phloem anatomy (e.g., number and size of conducting elements, thickness of xylem cell walls), measurements of common morphological traits (e.g., stem diameter, tree height, crown size). Allometric approaches are used to define optimality principles shaping the hydraulic structure of trees (e.g., xylem/phloem widening in leaves, stems, roots) and the structure of forest ecosystem; dendroecological approaches are used to assess climate-growth relationships from time series of tree ring traits. (T. Anfodillo, M. Carrer, D.Castagneri, G.Petit).
   
   
4. Forest analysis.
   Forest structure analysis by LiDAR and optical data, Soil ecology and radiative balance, Analysis of forest parameters using remote sensing and geographic information systems. (F.Pirotti, E.Lingua, A. Zanella).
   
   
5. Geomatics for forest and the environment.
   Measuring via sensing (remote and close-range) of natural and man-made environments; 3D models for virtual/augmented reality of scenery, active (SAR/InSAR/PolSAR/LiDAR) and passive remote sensing for Earth Observation (EO), spatio-temporal analysis of big-data via High Performance Computing applied to sensed data. (F.Pirotti).
   
   
6. Urban forestry.
   Landscape-forest patterns and processes in urban and suburban areas. Urban forests biodiversity and recreational use. (T. Sitzia, T. Campagnaro).
   
   
7. Forest landscape restoration.
   Monitoring and assessment of forest recovery and restoration by natural regeneration and afforestation activities. Implementation of restoration strategies using assisted regeneration and applied nucleation concepts. Restoration of forest cover in stands affected by high severity disturbances by using biological legacies. (T. Sitzia, E. Lingua).
   
   
8. Wood technologies.
   Wood characterization and synthesis of bio-based adhesives and preservatives for enhancing its properties by producing eco-friendly but also performing timber composites. Evaluation of the environmental impact of different materials and process through life-cycle assessment  (LCA) tools. (G.Tondi, M.Zanetti).
   
   
9. Forest planning and landscape ecology.
   The study of forest landscape patterns and its relationship with planning and management of land uses in the framework of landscape ecological methods and tools. (E. Lingua, T. Sitzia).
   
   
10. Biodiversity monitoring  and conservation in different ecosystems.
    Relationship between biodiversity and degree of disturbance in forest ecosystems; effects of direct and indirect human activities on biodiversity decline; management and conservation of blue infrastructures; loss and modification of wetlands and effects on biodiversity in mountain areas; implementation of practices for restoring wetlands and increasing biodiversity (Anfodillo T, Sitzia T, Campagnaro T)

  Water resources, land and soil conservation

1. Erosion, debris flows and sediment transport in mountain watersheds: from processes and landform analysis to risk management, accounting for climate change.
   Monitoring and modeling of landslides, debris flows and debris floods occurrence including the rainfalls and its statistical extremes. Analysis of the impact of these phenomena for the scenario corresponding to the climate change. Risk mitigation measures: from active (early warning system) to passive (open check dams and retention basins). (L. Picco, V.D’Agostino, C.Gregoretti, M. Borga, P.Tarolli, A.Guarnieri).
   
   
2. Fluvial morphology, riparian vegetation, streams dynamics and restoration.
   Analyses on the morphodynamics of riverine corridors from the mountain to the lowlands. Monitoring of the interactions between riparian vegetation, channel morphology, and fluxes (water, sediment, and wood). Defining mitigation strategies for reducing risks in correspondence of critical sections (ie, bridges and embanked reaches), or to improve the general condition of the overall state of the river system (i.e., restoration). (L.Picco, V.D’Agostino, C.Gregoretti).
   
   
3. Soil, Water and Society.
   Economic losses caused by hydrological extremes, such as floods and droughts, are exacerbating because of increased anthropogenic activities and global environmental changes. The topic aims to understand how individuals and communities interact with hydrological extremes to develop effective strategies for disaster risk reduction. (P.Tarolli, M.Borga, V.D’Agostino).
   
   
4. Forest hydrology and ecohydrology.
   Analysis of the hydrological response of mountain catchments at the seasonal and event timescale by considering variations due to climate change, monitoring and modeling of water fluxes in the soil-plant-atmosphere continuum by using environmental tracers (stable isotopes of hydrogen and oxygen, major ions), analysis of the hydrological connectivity of intermittent streams during dry and wet conditions. (G.Zuecco, M.Borga).
   
   
5. Cryospheric processes and water resources in a warming climate.
   Climatic sensitivity of mountain snow, glaciers and permafrost investigated by historical analyses and reconstructions, current response monitoring, and process understanding. Investigation and modelling of future cryosphere-related changes in water resources, slope instability and environmental conditions. (L. Carturan, M.Borga).
   
   
6. Assessment of drought impact in agriculture: monitoring and mitigation strategies (P. Tarolli, M. Borga, V.D’Agostino).
   The project aims to investigate drought with its possible direct and indirect impacts in agriculture. The research focus ranges from farm to continental scales. Different agricultural landscapes, from lowland areas to steep slopes, will be considered in the analysis. In addition, sustainable solutions for mitigation of impacts and definition of adaptation strategies will be explored, including Nature Based Solutions.

  Technologies and operations for Agriculture, Forestry, Food and Livestock Plants

1. Sustainable wood harvesting in mountain forests.
   Precision forestry and digital solutions for the implementation of more sustainable wood harvesting operations in mountain forests in the frame of the climate change impacts. Novel applications based on Machine learning and Artificial intelligence are the main stream characterizing the research approach. (Grigolato S., Marchi L.).
   
   
2. Sustainable and digital approaches to agricultural technologies.
   Precision agriculture and digital solutions in agriculture, viticulture, water, and urban green management for enhancing sustainability in changing climate scenarios. Artificial intelligence and machine learning for advanced operations management and farm machinery. (Sartori L., Bortolini L., Marinello F., Sozzi M.).
   
   
3. Development of mechanical and digital technologies to enhance food quality.
   Novel application of mechanical devices, sensors, digital solutions, and data analysis to increase safety, security, and nutrient profile of foods. More sustainable food production processes through the application of technology. (Guerrini L.).
   
   
4. Innovative Systems/Technologies in Livestock and Bioenergy Production.
   Precision Livestock Farming (PLF), Digital and Automated Technologies for increased efficiency and reduced environmental impact. Bioresource Management and Valorisation (Bioenergy and sustainable biorefinery approaches) from agricultural and livestock systems. Utilisation of Remote Sensing and Spatial Data in Livestock/Energy Bioresource Supply Chain Research. (Pezzuolo A.).

  Enology, food quality and nutrition

1. Novel foods, food processing and nutrition.
   Development of novel foods. Novel bioactive food ingredients.  Functional properties of food macromolecules; Innovative techniques for food production and preservation; Food physics and rheology. Sensory analysis. Food and nutrition: food digestibility, functional and fortified foods. (G. Pasini, A. Curioni, G. Lomolino, M.Marangon).
   
   
2. Comprehending and managing wine quality.
   Wine macromolecules and colloids. Wine stability. Sustainable wine production systems. Innovation in sparkling winemaking. Proteomics and metabolomics of grapes and wines. Enological potential of disease-resistant grape varieties. Wine sensory analysis. Novel processing aids and additives for winemaking. Data management. (A. Curioni, S. Vincenzi, G. Lomolino, M. Marangon, R. Flamini).
   
   
3. Circular economy for the food and wine sectors.
   Valorization of by-products from the agri-food sector: novel extraction methods, chemical and functional characterization of extracts and their use as a source of novel food ingredients. (A. Curioni, S. Vincenzi, G. Lomolino, M. Marangon, G. Pasini).

  Forest Pathology

1. Engineered mycelium-based composite materials for environmental sustainability.
   Mycelium-based materials have the potential to contribute to the circular bioeconomy by replacing petroleum-based products and converting lignocellulosic wastes into value-added products. (Montecchio L., Linaldeddu B.).
   
   
2. Patterns of invasive forest pathogens dispersal by insects.
   The spread of fungal pathogens relies on complex interactions between host, vector (passive or active) and pathogen. Invasive insect-vectored pathogens pose one of the greatest threats to forest ecosystems. (Montecchio L., Linaldeddu B.).
   
   
3. The impact of climate change on forest tree diseases.
   Environmental changes are occurring on a global scale, but their effects are most pronounced in climate change hotspots. In the Mediterranean area canker causing agents such as Botryosphaeriaceae seem to thrive under warmer and drier conditions. (Montecchio L., Linaldeddu B.).
   
   
4. Emerging Phytophthora-related diseases in the subalpine European vegetation.
   The recent discovery of new Phytophthora species and diseases in alpine and subalpine ecosystems in Europe is of great concern. More explorations in the canopies of shrub and trees are needed to elucidate the diversity, host associations and Phytophthora lifestyles in these as yet under-explored habitats. (Montecchio L., Linaldeddu B.).