Restoration prioritization of sand grassland target

Spatial prioritisation of sandy grassland restoration using GIS-based expert models

The implementation of the EU Nature Restoration Regulation requires spatially explicit planning tools that help identify where restoration interventions can be most effective at national scale. In Hungary, sandy grasslands of the Danube–Tisza Interfluve represent highly threatened habitats, many of which have been converted to arable land or are otherwise degraded. At the same time, previous research has shown that regeneration potential varies considerably across the landscape.

This MSc project builds on earlier national-scale modelling work on the regeneration capacity of sandy habitats (Csákvári et al. 2019, 2021, 2022) and aims to further develop a GIS-based expert system to support restoration prioritisation. The existing framework identifies areas where sandy habitats may potentially be restored based on environmental suitability and landscape context. The current task is to refine, validate, and further develop this decision-support approach.

The MSc student will work primarily with spatial datasets and modelling outputs in a GIS environment. The main components of the project include: 1. Integration and spatial filtering of environmental predictor layers (e.g. soil properties, sand content, landscape naturalness), and incorporation of climate projection data into the prioritisation framework. 2. Identification and validation of critical abiotic threshold values that determine the potential occurrence of sandy habitats. 3. Further development of the naturalness indicator, including clarification of the role of invasive species in shaping restoration feasibility. 4. Improvement and testing of rule-based decision trees that classify areas according to restoration potential.

Optional development task (advanced level): Creation of a simplified web-based expert interface where users can select input variables and receive recommendations on which habitat type could be feasibly restored at a given location.

The ideal candidate has a background in ecology, environmental sciences, geography, or a related field, with strong interest in ecological restoration and spatial planning. Experience with GIS software (e.g. QGIS or ArcGIS) is essential. Basic skills in statistical analysis (e.g. R or similar) are expected. Interest in modelling approaches and decision-support systems is an advantage. Programming skills or experience with web-based tools are welcome but not required.

The MSc thesis is expected to produce a refined and validated spatial prioritisation framework for sandy grassland restoration with a documented and reproducible GIS-based workflow. Potential contribution to a peer-reviewed publication.

Further information: Melinda Halassy (halassy.melinda@ecolres.hu)

Selected literature: 

Csákvári, E., Molnár, Z., & Halassy, M. (2022). Estimates of regeneration potential in the Pannonian sand region help prioritize ecological restoration interventions. Communications Biology, 5(1), 1–11.

Csákvári, E., Bede-Fazekas, Á., Horváth, F., Molnár, Z., & Halassy, M. (2021). Do environmental predictors affect the regeneration capacity of sandy habitats? A country-wide survey from Hungary. Global Ecology and Conservation, 27, e01547.

Csákvári, E., Horváth, F., Molnár, Zs., & Halassy, M. (2019). National-level assessment of the regeneration capacity of sandy habitats. In: Fazekas, I., & Lázár, I. (eds.), Landscape functioning and structure. Debrecen. Pp. 231-236.