Adapting a multiscale approach to assess the compositional diversity of landscapes

Abstract

Context The role of landscape diversity and structure is crucial for maintaining biodiversity. Both landscape diversity and structure have often been analysed on one thematic layer, focusing on Shannon diversity. The application of compositional diversity, however, has received little attention yet. Objectives Our main goal was to introduce a novel framework to assess both landscape compositional diversity and structure in one coherent framework. Moreover, we intended to demonstrate the significance of the use of a neutral model for landscape assessments. Methods Both entire Hungary and nine of its regions were used as study areas. Juhász-Nagy’s information theory-based functions, i.e. “compositional diversity” and “associatum”, were introduced and applied in landscape context. Potential and actual landscape characteristics were compared by analysing a probabilistic representation of potential natural vegetation (multiple PNV, MPNV) and actual vegetation (AV), treating MPNV as a neutral model. Results A significant difference was found between the MPNV- and AV-based, maximal compositional diversity estimates. MPNV-based maximal compositional diversity was higher and the maximum appeared at a finer spatial scale. The differences were more prominent in human-modified regions. Associatum implied the spatial aggregation of both MPNV and AV. Fragmentation of AV was indicated by larger units carrying maximal compositional diversity and maximal associatum values. Conclusions Applying the multiscale Juhász-Nagy’s functions to landscape composition allowed more precise characterization of the landscape state than traditional Shannon diversity. Our results underline, that increasingly transformed landscapes host decreasing complexity of vegetation type combinations and increasing grain that carries the richest information on landscape vegetation patterns.