DOI: 10.5061/dryad.n02v6wwtx
title: Data from: Factors affecting carcass detection at wind farms using dogs and human searchers

description: 1. The use of detection dogs to effectively monitor bird and bat
 fatalities at wind farms is becoming increasingly popular. All studies to
 date agree that dogs outperform human searchers at finding bird and bat
 carcasses around wind turbines; however, it remains unclear how particular
 conditions during the search may influence carcass detection. 2. We
 investigate the effect of carcass size, habitat characteristics and
 weather conditions on carcass detection probability, for both dogs and
 humans, using data from the monitoring program of a wind farm in Spain. 3.
 A generalized linear model reveals a high performance of dogs (~80%
 detection probability), with no clear influence of any of the variables
 analysed. Humans, on the contrary, were markedly affected by the size of
 the carcass and to some extent, by the vegetation structure. Humans
 performed poorly at detecting small carcasses (~20% detection
 probability), more so in dense vegetation. 4. Synthesis and applications.
 Our results provide evidence that dogs perform at a high level under a
 wide range of environmental conditions. They are particularly well-suited
 for the monitoring of fatalities of small, rare or inconspicuous species
 in cluttered environments. Humans, by contrast, are very poor at detecting
 all but the largest carcasses.16-Jun-2020
description: We
 compared the effectiveness of dogs and humans searchers at finding bird
 and bat carcasses under wind turbines. We used two Belgian Malinois and
 one Border Collie, between 2 and 4 years old. We also used two human
 searchers (alternatively) who were experienced in searching for birds and
 bats at wind farms for the human detection trials. When a
 dog-handler team was to search at a turbine, the handler would place 1-3
 carcasses at allocated random locations. Carcasses would be thrown from a
 distance to avoid leaving a track on the ground that the dog could follow.
 To prevent the handler from giving any clues to the dog as to where the
 carcasses were placed, the handler always walked in a fixed search pattern
 during searches, at a constant pace and only communicated with the dogs to
 ensure they stayed within the search band. Handlers only approached and
 rewarded the dogs after they displayed a proper detection alert. The
 search pattern of the dog-handler team consisted of four parallel line
 transects on each search plot. The handler followed straight
 line transects traversing the search area, while the dog was allowed to
 move freely within approximately 10 meters at either side of the handler.
 Searches were conducted perpendicular to the wind direction to maximize
 the probability of coming in contact with the scent cone produced by the
 carcasses. An average of five wind turbines were surveyed per day.
 Detection trials were performed weekly from 24th January 2012 through to
 30th July 2013, in days without precipitations or strong winds. We
 conducted 589 detection trials, using 50 different species.
 Human
 trials followed the same procedure as dog trials, although in this case it
 was a helper who placed the carcasses prior to the search. Humans searched
 along 8-10 parallel line transects aiming to cover a 5 m wide band at each
 side of the transect. Trials for human searchers were conducted on a
 selection of 15 wind turbines out of the turbines searched by the dogs.
 Therefore, all turbines searched by humans were also searched by dogs but
 not the other way around. The sample of turbines searched by humans
 covered a similar proportion of habitats as those searched by the dogs.
 Humans surveyed 5 wind turbines per day. Fewer detection trials were
 conducted for human searchers than for dogs; between the 16th October 2012
 through to the 30th July 2013, on days without precipitations or strong
 winds, we conducted 121 detection trials using 28 different species.  We
 used the same range of carcass sizes, and in a similar proportion, for
 human and for dog detection trials. We used
 carcass species wingspan, as a measure of carcass size. To characterize
 the vegetation in each search plot, we measured six variables related to
 vegetation height and cover in four non-overlapping circular areas of 5 m
 radius. The location of the centre of these areas was defined randomly
 using a random point generator. For each measured variable, we took the
 average value of the four areas and used it as a covariate in the
 analysis. We used the daily mean wind speed (km/h) and mean temperature
 (°C) for the Masegoso municipality (one kilometre away from the nearest
 wind turbine), obtained from the meteorological web site www.eltiempo.es.  To reduce the dimensionality of the vegetation descriptors and to prevent multicollinearity in the models, we performed a principal component analysis (PCA)
description: Each row in the dataset corresponds to the search of one carcass.
 The dataset contains the following variables: - id:
 unique identifier of the search event. - detect: 1 -
 carcass detected, 2 - carcass not detected - date: date
 of the search - type: type of searcher - dog,
 human - ind: individual searcher: d1, d2, d3, h1,
 h2 - size: carcass species wingspan (cm)
 - turb: turbine at which the search was conducted
 - cobground: bare ground cover (%) -
 cobveg0_10: cover of vegetation between 0 and 10 cm high (%)
 - cobveg10_30: cover of vegetation between 10 and 30 cm
 high (%) - cobveg30_100: cover of vegetation between 30
 and 100 cm high (%) - cobveg100_300: cover of
 vegetation between 100 and 300 cm high (%)
 - cobveg300_: cover of vegetation higher than 300 cm
 (%) - temp: mean day temperature (degrees
 celsius) - wind: mean day wind speed (km/h)
 - pc1: vegetation structure principal component 1
 - pc2: vegetation structure principal component 1
 - pc3: vegetation structure principal component 1