TY - JOUR
T1 - Emerging topics and new directions in statistical ecology
AU - Altwegg, Res
AU - Salau, Sulaiman
AU - Abadi, Fitsum
AU - Cervantes, Francisco
AU - Clark, Allan E.
AU - Distiller, Greg
AU - Gimenez, Olivier
AU - Henry, Dominic A. W.
AU - Johnston, Alison
AU - Joo, Rocío
AU - Karenyi, Natasha
AU - Kuiper, Tim
AU - Marques, Tiago A.
AU - Ngwenya, Mzabalazo
AU - Oosthuizen, W. Chris
AU - Photopoulou, Theoni
AU - Slingsby, Jasper
AU - Sutherland, Chris
AU - Visser, Vernon
N1 - Funding: We acknowledge funding from the DSI-NRF Centre of Excellence in Mathematical and Statistical Sciences, the National Research Foundation (grant 136357) and the University of Cape Town. TAM thanks partial support by CEAUL (funded by FCT - Fundação para a Ciência e a Tecnologia, Portugal DOI: 10.54499/UIDB/00006/2020).
PY - 2025/5/29
Y1 - 2025/5/29
N2 - 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 remain key areas 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 more inclusive, and to promote rigorous data analysis practices that support reproducible research and transparent conservation decisions. As human pressures on nature intensify, statistical ecology is becoming an increasingly vital area of research.
AB - 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 remain key areas 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 more inclusive, and to promote rigorous data analysis practices that support reproducible research and transparent conservation decisions. As human pressures on nature intensify, statistical ecology is becoming an increasingly vital area of research.
KW - Data integration
KW - Ecological statistics
KW - International Statistical Ecology Conference
KW - Quantitative ecology
KW - Statistical ecology
KW - Structural topic model
U2 - 10.1007/s42519-025-00460-4
DO - 10.1007/s42519-025-00460-4
M3 - Article
AN - SCOPUS:105007088202
SN - 1559-8608
VL - 19
JO - Journal of Statistical Theory and Practice
JF - Journal of Statistical Theory and Practice
IS - 3
M1 - 44
ER -