Marta Bonato

Marta Bonato

PhD candidate

Helmholtz Centre for Environmental Research – UFZ
Department Computational Landscape Ecology
Permoserstraße 15
+49 341 235 1954

Research interests

  • Impacts of agricultural land use and management on biodiversity and ecosystem services
  • Landscape-scale analysis and planning
  • Stakeholders involvement
  • Climate change adaptation

 Curriculum Vitae

 Since 2020

PhD candidate at Computational Landscape Ecology Department

  • PhD Topic: "Moving toward multifunctional agricultural landscapes: a model-based approach that links landscape characteristics with natural pest control, water quality and crop production"

       Part of INTERCEDE PhD cohort

2019 - 2020

Research fellow, Ca´ Foscari University of Venice / CMCC Euro-Mediterranean Center on Climate Change

2018 - 2019

Visitor scientist, VU Amsterdam, Institute for Environmental Studies


Trainee, Joint Research Centre, Food Security Unit

2014 - 2017

M.Sc. in Environmental Sciences - Curriculum Evaluation and Management of Environmental Systems, Ca´ Foscari University of Venice

  • M.Sc. thesis: "High Nature Value areas individuation and ecosystem services evaluation in rural Veneto: a landscape scale analysis with GIS methodology"

2010 - 2013

B.Sc. in Sciences and Technology for the Environment, University of Padua


  • Bonato, M., Cian, F., Giupponi, C., (2019). Combining LULC data and agricultural statistics for a better identification and mapping of High Nature Value farmland: A case study in the Veneto Plain, Italy. In Land Use Policy, vol. 83, pp. 488-504 Link
  • Bonato, M., Sambo, B., Sperotto, A., Lambert J.H., Linkov, I., Critto, A., Torresan, S., Marcomini, A., (2021). Prioritization of Resilience Initiatives for Climate-Related Disasters in the Metropolitan City of Venice. In Risk Analysis  Link
  • Bonato, M. Bartkwoski B., Beckmann, M., Cord, A., Seppelt, R., Strauch, M., (2021). Understanding the effects of landscape complexity on natural pest control: potential and limitations of applying generic models to local case studies. In Book of abstract: Landscape 2021, online conference | 20-22 September 2021 Link


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