Self-sustainability status indicators of vegetation stands and types utilising Potential Natural Vegetation estimations

Gyalus, Adrienn and Bede-Fazekas, Ákos and Molnár, Zsolt and Somodi, Imelda (2026) Self-sustainability status indicators of vegetation stands and types utilising Potential Natural Vegetation estimations. ECOLOGICAL INDICATORS, 190. No. 115409. ISSN 1470-160X

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Abstract

Optimising conservation and restoration efforts calls for detailed assessment on the potential self-sustainability of vegetation types. We propose an indicator framework relying on matches and mismatches between predicted distributions of vegetation types and observed distributions. We examined the utility of all combinations of predicted and observed values, however, we introduced a five-rank scale to categorise predictions rather than simple presence/absence outputs. This yielded 10 possible indicator combinations, out of which nine was present in the dataset. We tested the indicators' applicability using countrywide observed vegetation data and potential natural vegetation estimates for Hungary. Indicators were subjected to Principal Component Analysis (PCA) to examine the interrelationships as well as mapped in space habitat-wise and as aggregated (synthetic) maps across vegetation types. Indicators were identified in relation to levels of unsuitability, uncertain presence, levels of potentiality, extinction debt and levels of self-sustainability in existing stands. Each indicator was found to correspond to an individual interpretation in terms of ecological insight (including potentiality and vegetation inertia), conservation and restoration optimisation. PCA results reinforced the finding with the first three components explaining 90% and 80% of the variation for the absolute count and relative count based indices respectively. Map representations proved to be informative on conservation and restoration priorities habitat-wise. Furthermore, our indices supported identification of conservation and restoration hotspots, as well as provided insights about the vulnerability of individual vegetation types. Identification of localities and spatial concentration of areas with predominantly self-sustaining or threatened vegetation has potential to support for conservation and restoration decisions.

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