Code and data for "Emerging topics and new directions in statistical ecology"

The dataset and accompanying R code provided in the R Markdown file linked to the following manuscript submitted for review: Altwegg et al. <i>"Emerging topics and new directions in statistical ecology"</i><i>.</i><b>Abstract of linked material:</b>Ecological science relies on robust estimates of the abundance, diversity, and spatial distribution of individuals and species, but these quantities are notoriously difficult to observe directly. Data collected on these quantities not only reflect the ecological processes giving rise to them but also the observation process, which is often biased by factors such as uneven sampling effort or imperfect detection. Furthermore, collecting data according to standard sampling designs is often not possible. Statistical ecology as a research field specialises in developing statistical methods for analysing such complex ecological data. Here, we apply text analysis tools to the abstracts submitted to eight International Statistical Ecology Conferences between 2008 and 2022 to guide a review of recent topics in statistical ecology. Results show that estimating various aspects of demography (including survival, recruitment, abundance, density and movement) and spatial distribution remains a key area of research. The field has benefited from and embraced new data collection methods such as automated recorders and rapidly developing remote sensing techniques. How to integrate data from different sources is a central challenge that spans multiple areas of statistical ecology. The statistical ecology community strives to be inclusive. It also promotes robust data analysis strategies that underpin reproducible research and transparent conservation decisions. With the increasing pressure of human society on nature, we feel statistical ecology is becoming an ever more important research field. <b>Files:</b>Data_Altwegg_et_al_JSTP_2025.csvData_Altwegg_et_al_JSTP_2025.rmd