4.7 Article

A sampling strategy for assessing habitat coverage at a broad spatial scale

Journal

ECOLOGICAL INDICATORS
Volume 143, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2022.109352

Keywords

Design -based inference; Italy; Monitoring; Precision estimation; Two-phase sampling; Two -stage sampling; Simulation study

Funding

  1. project Development of a National Plan for Biodiversity Monitoring (Italian National Institute for Environmental Protection and Research-ISPRA)

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The quantitative assessment of habitat conservation status is an important task for European Union member states. This study presents an adaptive monitoring approach based on a two-phase sampling scheme to estimate the coverage of EU terrestrial habitat types. The method has the potential to increase precision in estimating habitat coverage.
The quantitative assessment of habitat conservation status is a major task for European Union member states in compliance with Council Directive 92/43. One goal of the European 2030 Biodiversity Strategy is the effective management of habitats that show declining trends. While various approaches have been adopted for national assessments, there is no consensus on how to achieve common statistically sound estimates of the criteria indicated by the EU Directive for the evaluation of the status and trend of habitat types. Here, we present an adaptive monitoring approach based on a two-phase sampling scheme to estimate the coverage of EU terrestrial habitat types, which is one of the four criteria indicated by the Habitats Directive. We used 9 habitats distributed among different EU member states choosing Italy as a case study. The development of the methodological approach is described, and a simulation study was performed to check the precision of the coverage estimators accounting for the lack of sampled data (nonresponse treatment), subregions and sustainable sampling effort. We found that our two-phase sampling approach has the potential to increase precision in estimating the coverage of habitat types (approximated at 1 ha cell size) with respect to the precision achieved by simple random sampling without replacement, which is the simplest sampling approach. Adopting a small sampling fraction <= 0.04%) of the survey area, the relative standard errors ranged from 7 to 15% for common habitats whose presence is strongly correlated with the habitat suitability scores furnished by an expert team. In the challenging context of a mandated monitoring type, our approach provides sound statistical estimates of habitat coverage with the possibility of applying a standardised and transferable sampling scheme that is easily repeatable over time.

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