Enough Is Enough? Searching for the Optimal Sample Size to Monitor European Habitats: A Case Study from Coastal Sand Dunes

Abstract

A robust survey method that samples the main characteristics of plant assemblages is needed to assess the conservation status of European habitat in the Natura 2000 network. A measure of variability, called pseudo-multivariate dissimilarity-based standard error (MultSE), was recently proposed for assessing sample-size adequacy in ecological communities. Here, we used it on coastal sand dune systems in three Special Areas of Conservation (SACs) in Tuscany. Our aim was to assess the minimum number of replicates necessary to adequately characterize sand dune environments in terms of differences between habitats and SACs, after a preliminary baseline assessment of plant diversity. Analysis of α and β diversity indicated that especially between habitats the three SACs protect different plant communities. The study of the MultSE profiles showed that the minimum number of replicates needed to assess differences among habitats varied between 10 and 25 plots. Two-way PERMANOVA and SIMPER analysis on the full and reduced datasets confirmed that SACs and habitats host different plant communities, and that the contribution of the target species remained unchanged even with a reduced sample size. The proposed methodological approach can be used to develop cost-effective monitoring programs and it can be useful for plant ecologists and biodiversity managers for assessing ecosystem health and changes.

Shedding light on typical species: implications for habitat monitoring

“…Part of them were of technical nature and can be more or less easily implemented. The use of a probabilistic sampling design, such as the stratified random sampling design, could substantially increase the objectivity of the monitoring (McGarvey et al 2016;Corona et al 2020;Maccherini et al 2020), while the inclusion of other taxa and of other survey approaches (e.g., the dendrometric survey of forest vegetation; De Yao et al 2019) can provide valuable information on the habitat conservation status. Nevertheless, a probabilistic sampling design might not be effective for habitats characterized by a limited distribution and/or a linear surface which could be underrepresented.…”

Measuring Alpha and Beta Diversity by Field and Remote-Sensing Data: A Challenge for Coastal Dunes Biodiversity Monitoring

“…Furthermore, collecting extensive and representative data in the field could be hampered by the impossibility to reach some monitoring areas [5]. Systematically surveying and monitoring complex and dynamic ecosystems (e.g., coastal dunes or river banks) by conventional biodiversity field campaigns might not be possible due to high costs, challenges to access to some sampling sites and lack of historical data [6,7]. Such crucial limitations hamper implementing statistically sound monitoring schemes that are essential for better understanding and modelling biodiversity in space and time [8].…”

Recognition and Characterization of Forest Plant Communities through Remote-Sensing NDVI Time Series

“…We focused on the NDVI to establish a baseline for future studies that will also consider different spectral indices that could also be derived from other data sources (e.g., Sentinel-2). Phenoclusters could be used to monitor phenomena and characterize the dynamics of landscapes and ecosystems [30,61], to improve phytosociological sampling, and to develop cost-effective monitoring programs, such as that of Maccherini et al [67], especially in those areas lacking prior phytosociological knowledge (e.g., phytosociological databases/maps).…”