Species traits explain variation in detectability of UK birds

Capsule Heterogeneous detectability amongst species may impact multi-species bird surveys and if not accounted for, may bias community level conclusions. Estimates of detectability were produced for 195 UK bird species, and detectability was significantly affected by bird size, diet and habitat specialization. Aims To estimate detectability and understand which species traits may impact detectability. Methods We estimated the detectability of 195 species of birds in the UK using distance sampling methods and examined the average detectability of genetically related groups. We tested the significance of species traits in describing variation in detectability, whilst controlling for phylogenetic relationships. Results Passeriformes had the lowest median detectability of 0.37 and Charadriiformes the highest median detectability of 0.65, of the seven largest orders considered. Species most associated with closed habitats such as woodland and urban areas had the lowest detectability. Smaller species had lower detectability than larger species. Conclusion Heterogeneity in species detectability could lead to biased conclusions, particularly when calculating multi-species indices such as species richness or diversity. Accounting for detectability will be most important in studies that cover a wide range of habitat types or a diverse spread of taxa.

[1]  T. Gottschalk,et al.  Comparison of distance sampling and territory mapping methods for birds in four different habitats , 2011, Journal of Ornithology.

[2]  S. Buckland.  Introduction to distance sampling : estimating abundance of biological populations , 2001 .

[3]  L. Anjos,et al.  The Importance of Considering Bird Detectability for Assessing Biological Integrity , 2012 .

[4]  Frédéric Jiguet,et al.  Accounting for weather and time-of-day parameters when analysing count data from monitoring programs , 2008, Biodiversity and Conservation.

[5]  G. Thomas.  Phylogenetic distributions of British birds of conservation concern , 2008, Proceedings of the Royal Society B: Biological Sciences.

[6]  F. Jiguet,et al.  An Indicator of the Impact of Climatic Change on European Bird Populations , 2009, PloS one.

[7]  P. Keyser,et al.  Comparison of point counts and territory mapping for detecting effects of forest management on songbirds , 2013 .

[8]  Bruce A. Robertson,et al.  Evaluating food availability and nest predation risk as sources of bias in aural bird surveys , 2010 .

[9]  David L. Borchers,et al.  The influence of animal mobility on the assumption of uniform distances in aerial line-transect surveys , 2008 .

[10]  H. Southern,et al.  Handbook of the Birds of Europe, the Middle East and North Africa; the Birds of the Western Palearctic , 1978 .

[11]  A. Magurran,et al.  Measuring Biological Diversity , 2004 .

[12]  D. MacKenzie.  Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence , 2005 .

[13]  K. Pollock,et al.  A Field Evaluation of Distance Measurement Error in Auditory Avian Point Count Surveys , 2007 .

[14]  Kenneth H. Pollock,et al.  A novel field evaluation of the effectiveness of distance and independent observer sampling to estimate aural avian detection probabilities , 2008 .

[15]  H. Crick.  A bird-habitat coding system for use in Britain and Ireland incorporating aspects of land-management and human activity , 1992 .

[16]  D. Noble,et al.  Composite bird indicators robust to variation in species selection and habitat specificity , 2012 .

[17]  H. Brumm.  The impact of environmental noise on song amplitude in a territorial bird , 2004 .

[18]  W. Link,et al.  Observer differences in the North American Breeding Bird Survey , 1994 .

[19]  Theodore R. Simons,et al.  Comparison of breeding bird and vegetation communities in primary and secondary forests of Great Smoky Mountains National Park , 2006 .

[20]  Exploring the effects of truncated, pooled and sexed data in distance sampling estimation of breeding bird abundance , 2009 .

[21]  D. Bystrak.  The Breeding Bird Survey , 1979 .

[22]  M. Pagel,et al.  Phylogenetic Analysis and Comparative Data: A Test and Review of Evidence , 2002, The American Naturalist.

[23]  Richard J. Barker,et al.  Statistical aspects of modeling population change from population size data , 1994 .

[24]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[25]  M. Pagel.  Inferring the historical patterns of biological evolution , 1999, Nature.

[26]  K. Burnham,et al.  Program MARK: survival estimation from populations of marked animals , 1999 .

[27]  James D. Nichols,et al.  Monitoring of biological diversity in space and time , 2001 .

[28]  Anne E. Magurran,et al.  Goodness‐of‐fit measures of evenness: a new tool for exploring changes in community structure , 2011 .

[29]  S. Marsden.  Estimation of parrot and hornbill densities using a point count distance sampling method , 2008 .

[30]  R. Applegate,et al.  Problems with Avian Point Counts for Estimating Density of Northern Bobwhite—A Case Study , 2011 .

[31]  R. Peak.  A field test of the distance sampling method using Golden‐cheeked Warblers , 2011 .

[32]  S. Newson,et al.  Should we account for detectability in population trends? , 2013 .

[33]  Stephen T. Buckland,et al.  POINT-TRANSECT SURVEYS FOR SONGBIRDS: ROBUST METHODOLOGIES , 2006 .

[34]  The effect of observer experience on English Breeding Bird Survey population trends , 2010 .

[35]  R. L. Hutto,et al.  ESTIMATING DETECTION PROBABLITIES OF RIVER BIRDS USING DOUBLE SURVEYS , 2006 .

[36]  N. Barré,et al.  Standardising distance sampling surveys of parrots in New Caledonia , 2012, Journal of Ornithology.

[37]  David R. Anderson,et al.  Modeling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies , 1992 .

[38]  D L Borchers,et al.  Accommodating Unmodeled Heterogeneity in Double‐Observer Distance Sampling Surveys , 2006, Biometrics.

[39]  Korbinian Strimmer,et al.  APE: Analyses of Phylogenetics and Evolution in R language , 2004, Bioinform..

[40]  J. O'keeffe,et al.  Measuring Biological Diversity , 2004 .

[41]  S. Marsden,et al.  The Influence of Habitat, Season, and Detectability on Abundance Estimates across an Amazonian Parrot Assemblage , 2012 .

[42]  Aleksi Lehikoinen.  Climate change, phenology and species detectability in a monitoring scheme , 2012, Population Ecology.

[43]  Anne E. Magurran,et al.  Biological Diversity: Frontiers in Measurement and Assessment , 2011 .

[44]  K. Pollock,et al.  Effects of Vegetation and Background Noise on the Detection Process in Auditory Avian Point-Count Surveys , 2008 .

[45]  Theodore R. Simons,et al.  Testing the importance of auditory detections in avian point counts , 2009 .

[46]  Len Thomas,et al.  Distance software: design and analysis of distance sampling surveys for estimating population size , 2009, The Journal of applied ecology.

[47]  R. Green,et al.  Stone‐curlews Burhinus oedicnemus and recreational disturbance: developing a management tool for access , 2007 .

[48]  H. Brumm,et al.  Blackbirds sing higher-pitched songs in cities: adaptation to habitat acoustics or side-effect of urbanization? , 2009, Animal Behaviour.

[49]  F. Weller,et al.  Reduction of bias when estimating bird abundance within small habitat fragments , 2012 .

[50]  J. Greenwood,et al.  Use of distance sampling to improve estimates of national population sizes for common and widespread breeding birds in the UK , 2008 .

[51]  Guthrie S. Zimmerman,et al.  The Influence of Ecological Factors on Detecting Drumming Ruffed Grouse , 2007 .

[52]  John H. Giudice,et al.  Using time‐of‐detection to evaluate detectability assumptions in temporally replicated aural count indices: an example with Ring‐necked Pheasants , 2013 .

[53]  K. Pollock,et al.  EXPERIMENTAL ANALYSIS OF THE AUDITORY DETECTION PROCESS ON AVIAN POINT COUNTS , 2007 .

[54]  Frédéric Jiguet,et al.  Method learning caused a first‐time observer effect in a newly started breeding bird survey , 2009 .

[55]  J. Andrew Royle,et al.  ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.

[56]  Iris Broekema,et al.  Distance sampling to estimate densities of four native forest bird species during multi- species surveys , 2012 .

[57]  H. Jachmann.  Comparison of aerial counts with ground counts for large African herbivores , 2002 .

[58]  Len Thomas,et al.  IMPROVING ESTIMATES OF BIRD DENSITY USING MULTIPLE- COVARIATE DISTANCE SAMPLING , 2007 .

[59]  P. Marler,et al.  Nature's Music: The Science of Birdsong , 2004 .

[60]  T. Schweder.  Advanced Distance Sampling: Estimating Abundance of Biological Populations , 2007 .

[61]  Jim Schieck,et al.  Biased detection of bird vocalizations affects comparisons of bird abundance among forested habitats , 1997 .

[62]  A. Bronkhorst,et al.  Auditory distance perception in humans : A summary of past and present research , 2005 .

[63]  D. Dawson,et al.  Effect of Distance-Related Heterogeneity on Population Size Estimates from Point Counts , 2009 .

[64]  W. Brockelman,et al.  A Field Test of Distance Sampling Methods for a Tropical Forest Bird Community , 2009 .

[65]  Hans Slabbekoorn,et al.  Chapter 6 – Singing in the wild: The ecology of birdsong , 2004 .

[66]  Y. Mori,et al.  Urban noise and male density affect songs in the great tit Parus major , 2011 .

[67]  R. Waide,et al.  Tropical forest bird counts and the effect of sound attenuation , 1988 .

[68]  R. Ekblom.  Evaluation of the analysis of distance sampling data: a simulation study , 2010 .

[69]  E. Fuglei,et al.  Monitoring Svalbard Rock Ptarmigan: Distance Sampling and Occupancy Modeling , 2012 .