The research, conducted by Cristian Vasilică Secu of Alexandru Ioan Cuza University of Iaşi and Radu Gabriel Pîrnău of the Romanian Academy’s Iaşi Branch, addresses a stubborn methodological problem in pedodiversity studies. Diversity indices applied to soils are notoriously sensitive to the classification system used and to the quality and resolution of available soil maps. Comparing pedodiversity between regions therefore requires that all analyzed territories share the same cartographic scale and taxonomic framework—conditions that are rarely met in practice. The Romanian team’s solution was to work within a single national classification system, the Romanian System of Soil Taxonomy, and to maintain a consistent map scale of 1:750,000 throughout the analysis.

The study area itself is a natural laboratory for soil diversity. Romania’s macrorelief is organized around the Carpathian Mountains, which occupy the central part of the country and are surrounded by the Subcarpathian hills, plateaus, and peripheral plains. Surface lithology varies dramatically across these units: mountains feature a diverse assemblage of metamorphic, igneous, and sedimentary rocks; the Subcarpathians alternate depressions and hills; lowland plains are dominated by loess and loess-like deposits; and limestone and sandstone prevail in plateau regions. The climate is temperate continental, with mean annual temperature around 9.5°C and precipitation averaging 700 mm per year, though the southeastern Dobrogea region receives less than 400 mm annually while high mountains exceed 1,000 mm.

The spatial distribution of Romanian soils follows a distinct concentric zonation around the Carpathians. Mountain regions are characterized by acidic soils—Cambisols, Podzols, and Umbrisols—with Andosols appearing locally in volcanic areas of the Eastern Carpathians. The surrounding hills and plateaus are dominated by Luvisols and Phaeozems, which gradually transition into an extensive belt of Chernozems in the peripheral lowlands. Fluvisols accompany major river valleys, often co-occurring with Gleysols and saline soils such as Solonchaks and Solonetz. Notably, the relatively similar areal proportions of Cambisols, Luvisols, and Chernozems mirror the spatial distribution of the country’s main landforms.

Methodologically, the researchers began with the SIGSTAR-200 vector database, derived from the Soil Map of Romania at 1:200,000, which contains 1,878 polygons at the soil type–subtype level. They generalized this database to 1:750,000 and then simplified the type–subtype vector to soil types alone, reducing the polygon count to 1,232. The aggregation process dissolved insular subtype polygons into their dominant encompassing polygons—for example, Cambic and Luvic Chernozem were merged as Chernozem. Crucially, the researchers preserved the surface area of each taxonomic unit across both vectors to prevent aggregation errors, and they classified taxa into two groups: variable taxa, whose polygon numbers changed during simplification, and constant taxa, which remained unchanged and typically correspond to rare or endemic soils.

The entropy calculations then proceeded along three parallel tracks. Entropy was computed separately for variable taxa extracted from the soil type vector (Y_A) and the soil type–subtype vector (Y_B), and for constant taxa (Y_C), which are common to both. The joint entropy of simultaneous distribution captured the probability that polygons for soil type–subtypes share the same spatial distribution as soil types. Finally, the connectivity index R was adapted from a method originally applied to soils and land use, approaching 1 when polygon numbers for variable taxa do not differ substantially between the two taxonomic levels and tending toward 0 when differences are large. Statistical validation included the Wilcoxon Signed-Rank Test, the Shapiro–Wilk test for normality, and rarefaction analysis in PAST 5.0 to confirm that the number of taxa estimated from polygon counts matched the values considered in the study.

The results produced a hierarchy that differs markedly from the conventional geographic regions framework. When ranked by the connectivity index, the landform units order as follows: plains (0.17) < plateaus (0.23) < Carpathians (0.27) < Subcarpathians (0.28). This sequence diverges from the geographic regions hierarchy, suggesting that connectivity between taxonomic levels is not simply a function of area or taxonomic richness. Weak connectivity—below 0.25—characterized the Southern and Eastern Carpathians, the Western Plain, and the Transylvanian Depression, indicating that numerous subtypes participate in the formation of the soil cover in these regions or that soil complexes are present, particularly in high mountain areas above 2,000 meters where glacial landforms promote Podzols and Umbrisols.

In stark contrast, the Dobrogea Plateau in southeastern Romania—the country’s most arid region, receiving less than 500 mm of precipitation annually with extreme temperatures—recorded the highest connectivity index at 0.72, followed by transitional regions such as the Getic and Moldavian Subcarpathians. The researchers attribute this pattern to the low taxonomic variability of arid regions: fewer variable taxa mean that polygon counts show minimal differences between the type–subtype and type levels, producing a relatively homogeneous structure. Interestingly, the number of variable taxa in a region does not directly determine the connectivity index value; the Getic Subcarpathians and the Danube Delta both contain three variable taxa, yet their joint entropy values differ substantially (0.48 versus 0.59), which substantially affects the connectivity index.

Bivariate correlation analysis revealed that joint entropy showed a very strong association with the connectivity index (0.98), while the diversity index of variable taxa exerted only a weak influence on both joint entropy (0.39) and the connectivity index (0.46). Constant taxa formed a separate group with a weak relationship to the diversity index of variable taxa (0.22). These findings confirm observations from the literature that probability measures alone are not always sufficient to explain the complexity of spatial structures and must be complemented by indices that capture interactions and informational redundancy. The connectivity index emerges as a valuable tool not only for describing pedological diversity but also for understanding the structural stability of spatial relationships in regions with contrasting characteristics.

The study also highlights complex interactions between landforms and parent materials. While mountain regions exhibit higher diversity due to morphological variability—in the Eastern Carpathians, volcanic and sedimentary rocks support Andosols, Eutric Cambisols, and Luvisols, whereas crystalline schists and altitudes above 2,000 meters in the Southern Carpathians promote Podzols and Umbrisols—in plains, the control exerted by parent material becomes the determining factor in structuring pedodiversity. The Romanian Plain shows a higher connectivity index (0.38) than the Western Plain (0.27) despite covering a larger area, a mismatch explained by the uniformity of aeolian loess deposits and sandy loess in the eastern plain, where the lithology associated with the highest degree of aridity limits the evolution of Chernozems toward a greater diversity of subtypes. The researchers caution that describing a region using a single diversity index value limits the ability to capture the spatial complexity of soil landscapes—a broader conceptual issue, since pedodiversity has been regarded by some authors as a controversial concept due to methodological constraints and the difficulty of simultaneously integrating pedogenetic factors, spatial variability, and taxonomic classifications.

Subject of Research: Entropy-based pedodiversity and connectivity index analysis ranking Romania's geographic regions and landform units

Article Title: Ranking Territorial Units Using Entropy-Based Pedodiversity

Article References: Secu, C. V., & Pîrnău, R. G. (2026). Ranking Territorial Units Using Entropy-Based Pedodiversity. Spanish Journal of Soil Science, 16, Article 15664. https://doi.org/10.3389/sjss.2026.15664

Image Credits: AI Generated

DOI: 10.3389/sjss.2026.15664

Keywords: pedodiversity, connectivity index, joint entropy, Shannon entropy, soil taxonomy, GIS, Romania, Carpathians, soil maps, landform units, geographic regions, information theory