Professional summary

Rob is an ecological statistician specialising in sampling theory, missing data theory, causal inference and biodiversity monitoring. 

Selected publications

Boyd Robin J. et al. , (2025), Using causal diagrams and superpopulation models to correct geographic biases in biodiversity monitoring data. Methods in Ecology and Evolution, https://doi.org/10.1111/2041-210X.14492

Pescott Oliver L. et al. , (2025), Adaptive sampling for ecological monitoring using biased data: a stratum‐based approach. Oikos, https://doi.org/10.1002/oik.11115

Boyd Robin J. et al. , (2024), On the trade-off between accuracy and spatial resolution when estimating species occupancy from geographically biased samples. Ecological Modelling, 493, http://dx.doi.org/10.1016/j.ecolmodel.2024.110739

Boyd Robin J. et al. , (2023), Descriptive inference using large, unrepresentative nonprobability samples: an introduction for ecologists. Ecology, http://dx.doi.org/10.1002/ecy.4214

Boyd Robin J. et al. , (2023), We need to talk about nonprobability samples. Trends in Ecology & Evolution, http://dx.doi.org/10.1016/j.tree.2023.01.001

Boyd Robin J. et al. , (2023), Causal inference and large‐scale expert validation shed light on the drivers of SDM accuracy and variance. Diversity and Distributions, 29, 774-784, http://dx.doi.org/10.1111/ddi.13698

Boyd Robin J. et al. , (2023), An operational workflow for producing periodic estimates of species occupancy at national scales. Biological Reviews, 98, 1492-1508, http://dx.doi.org/10.1111/brv.12961

Boyd Robin J. et al. , (2022), ROBITT: a tool for assessing the risk-of-bias in studies of temporal trends in ecology. Methods in Ecology and Evolution, https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13857

Boyd Robin J. et al. , (2022), Inferring trends in pollinator distributions across the Neotropics from publicly available data remains challenging despite mobilization efforts. Diversity and Distributions, 28, 1404-1415, http://dx.doi.org/10.1111/ddi.13551

Boyd Robin J. et al. , (2021), occAssess: an R package for assessing potential biases in species occurrence data. Ecology and Evolution, 11, 16177-16187, http://dx.doi.org/10.1002/ece3.8299