Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science

Abstract

1. 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.2. 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.3. 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.4. 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.5. 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.

Study of biological communities subject to imperfect detection: bias and precision of communityN‐mixture abundance models in small‐sample situations

“…For example, local population densities can be underestimated, while extinction and colonization rates of populations may be overestimated (Moilanen 2002;Ke´ry et al 2013). Some have argued that imperfect detection need not always be considered provided that a study employs a standardized sampling design (Johnson 2008;Banks-Leite et al 2014). However, if absolute abundance needs to be estimated and/or if detection probability depends on covariates that also affect abundance, then detection probability must be accounted for in any modeling framework for estimating abundance (Ke´ry 2008;Ke´ry et al 2010;Yamaura 2013).…”

Is the Italian stream frog (Rana italica Dubois, 1987) an opportunistic exploiter of cave twilight zone?

“…Within each sector we recorded air temperature and humidity (measured with a Lafayette TDP92 thermo-hygrometer; accuracy: 0.1 °C and 0.1%) and the average incident light (obtained by averaging max and min illuminance recorded with a Velleman DVM1300 light meter; minimum recordable light: 0.1 lux). We recorded the abundance of Rana italica within sectors using visual encounter surveys (VES; Crump and Scott 1994) and adopting a standardized survey method (7.5 min/sector) which limits potential effects of imperfect species detection (Banks- Leite et al 2014. Using the same procedure (VES + standardized survey method), we assessed the presence of seven invertebrate species which potentially represent prey items for R. italica: one dipteran (Limonia nubeculosa Meigen, 1804), three spiders (Meta menardi (Latreille, 1804), Tegenaria Latreille, 1804 sp., Metellina merianae (Scopoli, 1763)), one cricket (Dolichopoda laetitiae Minozzi, 1920) and two gastropods (Chilostoma planospira (Férussac, 1832), Oxychilus draparnaudi (Beck, 1837)).…”

Urbanization Alters the Influence of Weather and an Index of Forest Productivity on Avian Community Richness and Guild Abundance in the Seattle Metropolitan Area

“…Our design is appropriate, especially for community studies, where many birds are naturally rare (Banks-Leite et al, 2014). Moreover, while distance sampling is often employed to determine and correct for imperfect detection in bird studies, the basic assumptions of this approach: (1) that birds do not move between the start of the survey and the time at which they are observed, (2) that measurements from the observer to the bird are exact, and (3) that sampled areas are homogeneous are violated in most field settings, including ours (Johnson, 2008;Hutto, 2016;Marzluff et al, 2016).…”

“…Moreover, while distance sampling is often employed to determine and correct for imperfect detection in bird studies, the basic assumptions of this approach: (1) that birds do not move between the start of the survey and the time at which they are observed, (2) that measurements from the observer to the bird are exact, and (3) that sampled areas are homogeneous are violated in most field settings, including ours (Johnson, 2008;Hutto, 2016;Marzluff et al, 2016). Although failure to correct abundance estimates for imperfect detection may create a bias toward underestimation of relative abundance, rarely does correction affect a study's findings (Banks-Leite et al, 2014). Indeed, correction did not affect conclusions concerning the abundance of birds across changing, developed, or reserve landscapes in our study .…”

“…This decision compromises our ability to estimate occupancy, while increasing our ability to more accurately measure relative abundance. In addition, because distance estimation is difficult and likely biased by undetected movement of birds in forested lands and because developed lands are heterogeneous, we opted to control for imperfect detection in study design rather than with post-hoc statistical adjustments (Banks-Leite et al, 2014). We employed several strategies to increase and equalize the detection of birds across our survey plots (see Section Methods).…”