Does secondary data suffice? Protected area conflict analysis in the era of the COVID-19 pandemic

Abstract The COVID-19 pandemic has affected an established way of analysing protected area (PA) conflicts. A compelled turn towards a broader use of secondary data evokes doubts about validity of the results unless restrictive assessment procedures are implemented. To address this need, we propose a three-fold (theory-, method-, and cross-scale simulation-driven) approach to assess usefulness of a state register dataset and a group of methods of the indicator analysis for recognizing PA conflict determinants at the regional and local level. With the ultimate aim to inform case study selection, we used 187 relevant indicators from the Polish Central Statistical Office register for a Lesser Poland region and processed them using principal component/exploratory factor and cluster analyses. We distinguished five types of PA conflict determinants in a region (‘urbanity’, ‘agriculture’, ‘tourism’, ‘small-scale entrepreneurship’ and ‘sprawl’) and respective groups of clusters comprising local-level units. Then, we selected one cluster to juxtapose the results with secondary data from another source (Internet content) for a specific PA. We confirmed that reported conflict issues corresponded with indicator-derived descriptors of the cluster. However, secondary data from the state register failed to address the key prerequisites of PA conflicts (parties’ interests and their mutual perception). Overall, our approach can serve as a proxy for a multi-level PA conflict determinant analysis in crisis conditions such as COVID-19, provided it synthesises the results of various methodological approaches, followed by in-person inquiries in the selected case studies.