Abstract

AbstractQuestionsForest classifications are tools used in research, monitoring, and management. In Finland, the Cajanderian forest site type classification is based on the composition of understorey vegetation with the assumption that it reflects in a predictable way the site's productive value. In Russia, the Sukachevian forest classification is similarly based on understorey vegetation but also accounts for tree species, soil wetness, and paludification. Here we ask whether Cajander's and Sukachev's forest types are effectively the same in terms of species composition, site productivity, and biodiversity.LocationBoreal forests on mineral soils in Finland and the Russian part of Fennoscandia.MethodsWe use vegetation and soil survey data to compare the Cajanderian and the Sukachevian systems in terms of the understorey community composition (that is supposed to define them), soil fertility and tree productivity (that they are expected to indicate), and biodiversity (that is of interest for conservation purposes). We create and employ class prediction models to divide Russian and Finnish sites into Cajander's and Sukachev's types, respectively, based on vegetation composition. We perform cross‐comparisons between the two systems by non‐metric multidimensional scaling ordination and statistical tests.ResultsWithin both systems, the site types formed similar, meaningful gradients in terms of the studied variables. Certain site types from the two systems were largely overlapping in community composition and arranged similarly along the fertility gradient and may thus be considered comparable.ConclusionsThe Cajanderian and the Sukachevian systems were both developed in the European boreal zone but differ in terms of the exact rules by which site types are determined. Our results show that analogous types between the systems can be identified. These findings aid in endeavours of technology and information transfer between Finnish and Russian forests for the purposes of basic or applied ecological research and forest management.

Highlights

  • Forest site type classifications are tools used in ecological and forestry research, forest resource monitoring, and forest management planning

  • Vegetation is assumed to reflect the specific combination of all the environmental factors that prevail on the site and contribute to site quality, and vegetation is thought to be a more informative indicator of site quality than any individual environmental factor (Cajander, 1949; Sukachev, 1960)

  • It formally takes into account temporally variable, secondary environmental factors, whereas Cajander's classification assumes that comparatively permanent, primary environmental factors are manifested in the vegetation even as secondary factors change over time

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Summary

| INTRODUCTION

Forest site type classifications are tools used in ecological and forestry research, forest resource monitoring, and forest management planning. In Sukachev's classification, forest types are determined based on several factors in addition to the understorey: the composition and structure of the tree stand, soil moisture, and site productivity (Fomin et al, 2017) It formally takes into account temporally variable, secondary environmental factors (e.g., tree species, microclimate), whereas Cajander's classification assumes that comparatively permanent, primary environmental factors (e.g., basic properties of the soil, macroclimate) are manifested in the vegetation even as secondary factors change over time. Anthropogenic changes, it is necessary to re-evaluate the functionality of classifications used to guide their management Both Cajander and Sukachev considered that mature forests assigned into the same type ought to be comparatively uniform in species composition, environmental responses, and site quality, and that forests of the same type ought to require similar management under the same economic objectives and constraints (Fomin et al, 2017). We expect species richness to differ less within than between site types

| METHODS
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Findings
| DISCUSSION
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