Summary1. Imperfect detection can seriously bias conventional estimators of species distributions and species richness. Plant traits, survey-specific conditions and site-specific characteristics may influence plant detection probability. However, the generality of the problems induced by imperfect detection in plants and the magnitude of this challenge for plant distribution studies are currently unknown. 2. We address this question based on data from the Swiss Biodiversity Monitoring, in which vascular plants are surveyed twice in the same year along a 2.5-km transect in 451 1-km 2 quadrats.Overall, 1700 species were recorded. We chose a random sample of 100 species from the 1700 species to determine general detection levels. To examine the relationship of covariates on detection, we chose a stratified random sample of 100 species from 886 species that were detected in at least 18 locations, with 25 each from four life-forms (LF): grass, forb, shrub and tree. Using a Bayesian multispecies site-occupancy model, we estimated occurrence and detection probability of these species and their relation to covariates. 3. Based on the random sample of 100 species, detection probability during the first survey ranged 0.03-0.99 (median 0.74) and during the second survey, 0.03-0.99 (median 0.82). Based on the stratified random sample of 100 species, detection probability during the first survey ranged 0.02-0.99 (median 0.87) and during the second survey, 0.01-1 (median 0.89). Detection probability differed slightly among the four LFs. In 60 species, survey season or elevation had significant effects on detection. We illustrated detection probability maps for Switzerland based on the modelled relationships with environmental covariates. 4. Synthesis. Our findings suggest that even in a standardized monitoring program, imperfect detection of plants may be common. With the absence of a correction for detection errors, maps in plant distribution studies will be confounded with spatial patterns in detection probability. We presume that these problems will be much more widespread in the data sets that are used for conventional plant species distribution modelling. Imperfect detection should be estimated, even in distribution studies of plants and other sessile organisms, to better control detection errors that may compromise the results of species distribution studies.

Summary1. Plant ecologists have been rather slow to appreciate the existence and the effects of imperfect detection probability in plants. Sources of heterogeneous detectability include differences in morphology or life-form, patch size, observers and survey effort. Understanding the relationship between such factors and detectability is crucial for the efficient design of new plant distribution studies and for the interpretation of existing ones. 2. We have studied the factors affecting detectability in a large permanent plot (24 ha) in East China where the true distribution of six shrub and tree species was known from a detailed earlier inventory. Two observers independently resurveyed and recorded detection and non-detection of each species in each 20 · 20 m sampling quadrat. A total of 288 quadrats were resurveyed (218 by observer A, 211 by observer B and 141 by both). We used generalized linear mixed modelling to study the relationships between detection and species, observer, survey effort and patch size. 3. Detectability of an occupied quadrat was remarkably low and ranged from 0.09 to 0.34 on average for the six shrub and tree species. Differences of detection among species were mainly as a result of distinctive morphology rather than life-form. There was no significant difference of overall detection probability between the two observers. Detectability increased to 0.95 as the survey path approached 20% area of the sampling quadrat and as a plant patch covered c. 19% of the area of the sampling quadrat. 4. Synthesis. Our results suggest that imperfect detection is much more widespread than currently acknowledged by most plant ecologists. We identify several sources of heterogeneity in detectability (species, survey effort and patch size) that ought to be considered when studying and modelling the distribution of plant species. Detectability should be accounted for in plant distribution studies to avoid spurious inferences.

Human activities have shaped large-scale distributions of many species, driving both range contractions and expansions. Species differ naturally in range size, with small-range species concentrated in particular geographic areas and potentially deviating ecologically from widespread species. Hence, species’ responses to human activities may be influenced by their geographic range sizes, but if and how this happens are poorly understood. Here, we use a comprehensive distribution database and species distribution modeling to examine if and how human activities have affected the extent to which 9,701 vascular plants fill their climatic potential ranges in China. We find that narrow-ranged species have lower range filling and widespread species have higher range filling in the human-dominated southeastern part of China, compared with their counterparts distributed in the less human-influenced northwestern part. Variations in range filling across species and space are strongly associated with indicators of human activities (human population density, human footprint, and proportion of cropland) even after controlling for alternative drivers. Importantly, narrow-ranged and widespread species show negative and positive range-filling relationships to these human indicators, respectively. Our results illustrate that floras risk biotic homogenization as a consequence of anthropogenic activities, with narrow-ranged species becoming replaced by widespread species. Because narrow-ranged species are more numerous than widespread species in nature, negative impacts of human activities will be prevalent. Our findings highlight the importance of establishing more protected areas and zones of reduced human activities to safeguard the rich flora of China.