Plants stand still but hide: imperfect and heterogeneous detection is the rule when counting plants

Abstract

O_LIThe estimation of population size and its variation across space and time largely relies on counts of individuals, generally carried out within spatial units such as quadrats or sites. Missing individuals during counting (i.e. imperfect detection) results in biased estimates of population size and trends. Imperfect detection has been shown to be the rule in animal studies, and most studies now correct for this bias by estimating detection probability. Yet this correction remains exceptional in plant studies, suggesting that most plant ecologists implicitly assume that all individuals are always detected. C_LIO_LITo assess if this assumption is valid, we conducted a field experiment to estimate individual detection probability in plant counts conducted in 1x1 m quadrats. We selected 30 herbaceous plant species along a gradient of conspicuousness at 24 sites along a gradient of habitat closure, and asked groups of observers to count individuals in 10 quadrats using three counting methods requiring progressively increasing times to complete (quick count, unlimited count and cell count). In total, 158 participants took part in the experiment, allowing an analysis of the results of 5,024 counts. C_LIO_LIOver all field sessions, no observer succeeded in detecting all the individuals in the 10 quadrats. The mean detection rate was 0.44 (ranging from 0.11 to 0.82) for the quick count, 0.59 for the unlimited count (range 0.18-0.87) and 0.74 for the cell count (range 0.46-0.94). C_LIO_LIDetection probability increased with the conspicuousness of the target species and decreased with the density of individuals and habitat closure. The observers experience in botany had little effect on detection probability, whereas detection was strongly affected by the time observers spent counting. Yet although the more time-consuming methods increased detection probability, none achieved perfect detection, nor did they reduce the effect on detection probability of the variables we measured. C_LIO_LISynthesis. Our results show that detection is imperfect and highly heterogeneous when counting plants. To avoid biased estimates when assessing the size, temporal or spatial trends of plant populations, plant ecologists should use methods that estimate the detection probability of individuals rather than relying on raw counts. C_LI

Plant phenotyping relevance

植物個体数の計数における検出確率を、複数の計数法・多数の観察者・反復データで評価しており、植物個体群サイズの測定法の妥当性検証が研究の中心です。

Code and data availability

The paper's data availability statement explicitly deposits all data (5,024 plant counts from 300 quadrats) and analysis code in a public GitHub repository, which is listed in allowed_urls.