Species traits explain variation in detectability of UK birds

Johnston, Alison; Newson, Stuart E.; Risely, Kate; Musgrove, Andy J.; Massimino, Dario; Baillie, Stephen R.; Pearce‐Higgins, James W.

doi:10.1080/00063657.2014.941787

Cited by 66 publications

(74 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The variability in survival estimates of small waders may reflect greater variability in detectability (Johnston et al . ) but smaller species may also vary more in true survival rates, given that they may encounter a greater range of predators (small species will also be vulnerable to small predators that will not take larger species) and energetic constraints.…”

Section: Discussionmentioning

confidence: 99%

Patterns and processes in shorebird survival rates: a global review

Méndez

Alves

Gill

et al. 2018

Ibis

View full text Add to dashboard Cite

PortugalChanges in demographic rates underpin changes in population size, and understanding demographic rates can greatly aid the design and development of strategies to maintain populations in the face of environmental changes. However, acquiring estimates of demographic parameters at relevant spatial scales is difficult. Measures of annual survival rates can be particularly challenging to obtain because large-scale, long-term tracking of individuals is difficult and the resulting data contain many inherent biases. In recent years, advances in both tracking and analytical techniques have meant that, for some taxonomic groups, sufficient numbers of survival estimates are available to allow variation within and among species to be explored. Here we review published estimates of annual adult survival rates in shorebird species across the globe, and construct models to explore the phylogenetic, geographical, seasonal and sex-based variation in survival rates. Models of 295 survival estimates from 56 species show that survival rates calculated from recoveries of dead individuals or from return rates of marked individuals are significantly lower than estimates from mark-recapture models. Survival rates also vary across flyways, largely as a consequence of differences in the genera that have been studied and the analytical methods used, with published estimates from the Americas and from smaller shorebirds (Actitis, Calidris and Charadrius spp.) tending to be underestimated. By incorporating the analytical method used to generate each estimate within a mixed model framework, we provide method-corrected species-specific and genusspecific adult annual survival estimates for 52 species of 15 genera.

show abstract

Section: Discussionmentioning

confidence: 99%

Patterns and processes in shorebird survival rates: a global review

Méndez

Alves

Gill

et al. 2018

Ibis

View full text Add to dashboard Cite

show abstract

“…Multi‐species studies have shown that detectability varies greatly from species to species on animal surveys (Kéry and Schmid , Kéry and Plattner , Johnston et al. ). Little, however, is known about underlying causes of interspecific variation in detectability, primarily because the vast majority of studies seeking to account for missed animals treat detectability as a nuisance parameter rather than a subject of interest.…”

Section: Introductionmentioning

confidence: 99%

Using species traits to predict detectability of animals on aerial surveys

Schlossberg

Chase

Griffin

2017

Ecological Applications

View full text Add to dashboard Cite

Abstract. In animal surveys, detectability can vary widely across species. We hypothesized that detectability of animals should be a function of species traits such as mass, color, and mean herd size. We also hypothesized that models of detectability based on species traits can be used to predict detectability for new species not in the original data set, leading to substantial benefits for ecology and conservation. We tested these hypotheses with double-observer aerial surveys of 10 mammal species in northern Botswana. We combined all 10 species and modeled their detectability with species traits (mass, mean herd size, color) as predictors while controlling for observer effects, vegetation, and herd size. We found support for effects of mass and an interaction between herd size and mean herd size on detectability. This model accurately predicted the ratio of herds detected by two observers vs. one observer for 8 of 10 species. To test whether a model based on species traits could be applied to a new species, we serially deleted each species from the data set, fit a trait-based model to the remaining nine species, and used this model to predict detectability for the deleted species. The model was able to reproduce the species-trait model for seven species and accurately predicted the ratio of detections by one or two observers for a different set of seven species; the model was successful by both measures for five species. To our knowledge, this represents the first time that a mechanistic model for detectability of animals has been used to predict detectability for new species. Prediction failed for species with extreme values of traits, suggesting that predicting detectability is not possible near or beyond the boundaries of one's data set. The approach taken in this paper can potentially be used with a variety of taxa and may provide new opportunities to apply detectability corrections where they have not been possible before.

show abstract

“…Given that the detectability of birds varies widely within this range (Johnston et al 2014), whilst Landscape Ecol that of butterflies should not, we additionally corrected the estimates of bird community structure for variation in detectability using distance sampling (Buckland et al 2001, see Davey et al 2012. Equivalent results were obtained when this detectability correction was not applied (Supplementary Material 2).…”

Section: Discussionmentioning

confidence: 99%

Patterns and causes of covariation in bird and butterfly community structure

Eglington¹,

Brereton

Tayleur

et al. 2015

Landscape Ecol

Self Cite

View full text Add to dashboard Cite

Context Variation in biological communities is used to identify biodiversity responses to anthropogenic drivers, and to guide conservation responses. Often, such data are only available for a limited group of species, with uncertain applicability to unmonitored taxa. Objective Using equivalent data on the community structure of two contrasting taxa, we examine spatial co-variation in both communities, and test the extent to which any associations may result from large-scale latitudinal patterns, variation in habitat-type, or other factors. Methods Birds and butterflies were surveyed using standard methods across a stratified random sample of 1-km 2 squares across the UK. Four measures of community structure were calculated and used to examine their association between the two taxa, before accounting for effects of latitude, habitat-type and observer. Results Species richness, diversity and community specialisation were significantly correlated between birds and butterflies, but evenness was not. There were strong latitudinal gradients in bird community specialisation, and butterfly richness and diversity. Habitat diversity significantly affected bird communities, whilst butterfly evenness and specialisation was reduced on farmland and human-related habitats. Covariation in richness and diversity between taxa remained after including effects of latitude and habitat-type. Conclusions Surrogacy approaches may be useful when considering fine-scale variation in species richness and diversity to inform site-based conservation and management decisions. However, limited covariance in evenness and specialisation metrics suggest that decisions based on the needs of rare or specialist species may be less relevant to other taxa.

show abstract

Species traits explain variation in detectability of UK birds

Cited by 66 publications

References 59 publications

Patterns and processes in shorebird survival rates: a global review

Patterns and processes in shorebird survival rates: a global review

Using species traits to predict detectability of animals on aerial surveys

Patterns and causes of covariation in bird and butterfly community structure

Contact Info

Product

Resources

About