Climate warming has triggered shifts in plant distributions, resulting in changes within communities, characterized by an increase in warm-demanding species and a decrease in cold-adapted species - referred to as thermophilization. Researchers conventionally rely on co-occurrence data from vegetation assemblages to examine these community dynamics. Despite the increasing availability of presence-only data in recent decades, their potential has largely remained unexplored due to concerns about their reliability. Our study aimed to determine whether climate-induced changes in community dynamics, as inferred from presence-only data from the Global Biodiversity Information Facility (GBIF), corresponded with those derived from co-occurrence plot data in Norway. To assess the differences between these datasets, we quantified a Community Temperature Index (CTI) from the co-occurrence data set and compared this with CTI obtained from presence-only data. We also examined the temporal trend in CTI (i.e., thermophilization) in both datasets. To do this, we first established a species-temperature relationship based on data before climate warming. In a preliminary analysis, we assessed the performance of this relationship using three datasets: 1) Norwegian co-occurrence data, 2) presence-only data from a broader European region organized into pseudo-plots (potentially capturing more species niches), and 3) a combined dataset merging 1) and 2). The transfer function including both datasets performed best. Subsequently, we compared the CTI for the co-occurrence plots paired up spatially and temporally with presence-only pseudo-plots. The results demonstrated that presence-only data can effectively evaluate species assemblage responses to climate warming, with consistent CTI and thermophilization values in comparison to co-occurrence data. Employing presence-only data for evaluating community responses opens up better spatial and temporal resolution and much more detailed analyses of such responses, our results therefore outline how a large amount of presence-only data can be used to enhance our understanding of community dynamics in a warmer world.

Cyberinfrastructures in ecology have coevolved alongside fields excellent at expanding the landscape of big data acquisition. Arguably, they offer better technological solutions for mobilising ‘born digital’ data (e.g. sensor technologies and citizen science), then they do for low velocity, resource intensive ecological data which are inherently tied to sociological and cultural constraints limiting sharing. Such barriers can be summarised as trust, transparency and control, fundamental properties on which blockchain technologies have been prefiguratively designed. While this nascent decentralised ledger technology (DLT) is receiving increasing attention among the sciences, focus is yet to be directed at its potential utility to bolster open ecological data. In this viewpoint we offer insight into how blockchain technology could be leveraged to help normalise and incentivize open ecological data and its potential to help culture a paradigm shift from data proprietorship towards data stewardship.