Temporal changes in spatial scale and autocorrelation structure of forest openings based on taxonomic, phylogenetic, and functional turnover

Author:

Barfknecht David F.1,Heikens Alice L.2,Gibson David J.1

Affiliation:

1. Southern Illinois University

2. Franklin College

Abstract

Abstract Context During European settlement, Illinois grasslands were converted for agricultural purposes. Remaining natural areas in southern Illinois include natural xeric forest openings, with communities representative of remnant grasslands and adjacent hardwood forests. Previous research in these openings shows plant communities are driven by edaphic conditions.Objectives The first objective aimed to characterize spatial scale and autocorrelation structure of these openings based on climatic, environmental, and diversity variables. The second objective was to predict taxonomic, phylogenetic, and functional turnover between 1988 and 2019, using climatic and environmental variables.Methods Surveys were conducted to calculate taxonomic diversity and phylogenetic and functional trait analyses were used to calculate phylogenetic and functional diversity. Spatially-explicit climatic and environmental variables were included from earlier surveys and data repositories. Global Moran’s I and spatial autocorrelograms were used to assess spatial structure of climatic, environmental, and diversity variables and generalized dissimilarity modeling was used to characterize taxonomic, phylogenetic, and functional turnover based on environmental variables.Results Soil depth as the only environmental variable which exhibited significant global spatial autocorrelation. Climate variables and diversity metrics exhibited significant spatial structure during surveys. Generalized dissimilarity models showed that geographic distance between openings was the most influential driver of turnover across surveys.Conclusions Previous glacial events explained the spatial structure of soil depth across sites, due to Quaternary loess deposition in loess sites. High diversity values were clustered in the southeastern portions of the study area. Functional generalized dissimilarity models best predicted turnover in these openings compared to taxonomic and phylogenetic models.

Publisher

Research Square Platform LLC

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