Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science
Article first published online: 2 JUN 2014
© 2014 The Authors. Journal of Applied Ecology © 2014 British Ecological Society
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Journal of Applied Ecology
Volume 51, Issue 4, pages 849–859, August 2014
How to Cite
Banks-Leite, C., Pardini, R., Boscolo, D., Cassano, C. R., Püttker, T., Barros, C. S., Barlow, J. (2014), Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science. Journal of Applied Ecology, 51: 849–859. doi: 10.1111/1365-2664.12272
- Issue published online: 17 JUL 2014
- Article first published online: 2 JUN 2014
- Accepted manuscript online: 17 APR 2014 09:32AM EST
- Manuscript Accepted: 14 APR 2014
- Manuscript Received: 22 OCT 2013
- Natural Environment Research Council. Grant Number: NE/H016228/1
- Marie Curie International Incoming Fellowship
- biodiversity conservation;
- capture–recapture models;
- detection probability;
- imperfect detection;
- occupancy models;
- species richness
- In recent years, there has been a fast development of models that adjust for imperfect detection. These models have revolutionized the analysis of field data, and their use has repeatedly demonstrated the importance of sampling design and data quality. There are, however, several practical limitations associated with the use of detectability models which restrict their relevance to tropical conservation science.
- We outline the main advantages of detectability models, before examining their limitations associated with their applicability to the analysis of tropical communities, rare species and large-scale data sets. Finally, we discuss whether detection probability needs to be controlled before and/or after data collection.
- Models that adjust for imperfect detection allow ecologists to assess data quality by estimating uncertainty and to obtain adjusted ecological estimates of populations and communities. Importantly, these models have allowed informed decisions to be made about the conservation and management of target species.
- Data requirements for obtaining unadjusted estimates are substantially lower than for detectability-adjusted estimates, which require relatively high detection/recapture probabilities and a number of repeated surveys at each location. These requirements can be difficult to meet in large-scale environmental studies where high levels of spatial replication are needed, or in the tropics where communities are composed of many naturally rare species. However, while imperfect detection can only be adjusted statistically, covariates of detection probability can also be controlled through study design. Using three study cases where we controlled for covariates of detection probability through sampling design, we show that the variation in unadjusted ecological estimates from nearly 100 species was qualitatively the same as that obtained from adjusted estimates. Finally, we discuss that the decision as to whether one should control for covariates of detection probability through study design or statistical analyses should be dependent on study objectives.
- Synthesis and applications. Models that adjust for imperfect detection are an important part of an ecologist's toolkit, but they should not be uniformly adopted in all studies. Ecologists should never let the constraints of models dictate which questions should be pursued or how the data should be analysed, and detectability models are no exception. We argue for pluralism in scientific methods, particularly where cost-effective applied ecological science is needed to inform conservation policy at a range of different scales and in many different systems.