Plant diversity changes in a nature reserve: a probabilistic sampling method for quantitative assessments

Abstract

Species pool conservation is critical for the stability of ecosystem processes. However, climate and land use changes will likely affect biodiversity, and managers of protected areas are under increasing pressure to monitor native species diversity changes by approaches that are scientifically sound and comparable over time. Here we describe a plant diversity monitoring system in use since 2002 in the “Montagna di Torricchio” Nature Reserve (LTER_EU_IT_033), a Central Apennines representative area of 317 ha, most of which is under strict protection. The aim of this paper was to assess changes in plant species richness over time and to deduce the patterns of species assemblage. The monitoring system was based on a probabilistic sampling design representative of the different physiognomic vegetation types occurring in the Reserve. A total of 34 plots (10×10m) were sampled in 2002, 2003 and 2015, and their species presence/absence and relative coverage were estimated. Repeated measure ANOVA was used to test for plot-level and ecosystem-based changes in species richness along the study period. Temporal nestedness and temporal turnover metrics were used to assess patterns of species’ compositional changes. The results showed significantly different levels of species richness depending on the year, with the lowest value in 2003, probably linked to extreme drought events. Forest systems were comparatively stable, demonstrating the capacity to buffer interannual climate variability. Regarding compositional changes along the entire period (2002–2015), we found random patterns of both temporal nestedness and turnover, indicating stability in species composition. However, we also showed the contemporary occurrence of species loss and species replacement processes, considering the dry year 2003, a finding which should be further explored through fine-scale studies to unravel mechanisms of community assembly under drought. The use of a probabilistic sampling design representative of the different physiognomic vegetation types proved to be advantageous in monitoring the Nature Reserve vegetation and collecting reliable quantitative information. This data, in turn, provides the basis for improvements in management practices and proposed adaptation measures.