Conservation In Practice |
Corresponding author: Fabio Mosconi ( fabio.mosconi@gmail.com ) Academic editor: Marco Bologna
© 2017 Fabio Mosconi, Alessandro Campanaro, Giuseppe Maria Carpaneto, Stefano Chiari, Sönke Hardersen, Emiliano Mancini, Emanuela Maurizi, Simone Sabatelli, Agnese Zauli, Franco Mason, Paolo Audisio.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Mosconi F, Campanaro A, Carpaneto GM, Chiari S, Hardersen S, Mancini E, Maurizi E, Sabatelli S, Zauli A, Mason F, Audisio P (2017) Training of a dog for the monitoring of Osmoderma eremita. In: Carpaneto GM, Audisio P, Bologna MA, Roversi PF, Mason F (Eds) Guidelines for the Monitoring of the Saproxylic Beetles protected in Europe. Nature Conservation 20: 237-264. https://doi.org/10.3897/natureconservation.20.12688
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One aim of the MIPP Project (http://www.lifemipp.eu) was to develop non-invasive monitoring methods for selected saproxylic beetles. In this paper, a method is proposed for monitoring the larvae of Osmoderma eremita in their natural habitat (i.e. hollow trees), using a conservation detection dog (CDD). Wood mould sampling (WMS), the standard method to detect hermit beetles and other saproxylic insects inside tree hollows, is time-consuming and exposes the target species and the whole saproxylic communities to some risks. In contrast, CDDs pose no risk to the species living inside trees while, at the same time, offer a powerful tool for surveying the insects. In this paper, the methods applied to train the dog are presented, together with the results for accuracy (the overall proportion of correct indications), sensitivity (the proportion of correct positive indications) and specificity (the proportion of correct negative indications) obtained once the CDD had been fully trained. Results are presented for nitrocellulose filters with the odour of the target species, for larvae living inside hollow trees, for frass and for the remains of adults. A comparison of the efficiency between CDD and WMS showed that employing the dog was much less time-consuming than WMS.
The literature on training CDDs for nature conservation tasks, with particular reference to cases involving Coleoptera, was also reviewed.
Conservation detection dog, Osmoderma eremita, saproxylic beetles, Habitats Directive, monitoring methods, conservation biology
In the last few decades, conservation detection dogs (CDDs) (
Concerning invertebrates, pest, alien and invasive insect species are the main targets and indeed, conservation dogs were used for the first time to detect the gypsy moth Lymantria dispar (Linnaeus, 1758) (
In the LIFE Project MIPP (Monitoring of Insects with Public Participation, www.lifemipp.eu, Action A.4: “Acquisition and training of Osmodog”), a CDD was trained to find the larval stages of the hermit beetle Osmoderma eremita (Scopoli, 1763) in its natural habitat (see
The CDD of the MIPP project is the first case of a dog searching for an endangered beetle species, O. eremita. Indeed, a special feature of conservation dogs is that they can detect cryptic and/or elusive species (
Searching for larvae has some additional advantages as adults have a short period of activity (
The choice of the right dog is critical to the success in the training for finding insects. First of all, a dog must have a suitable drive for the specific task required and these motivational characteristics differ between breeds. As indicated by
It is preferable to use adult dogs for the fieldwork as juvenile dogs may have lower levels of attention and concentration than adults (
Living targets, in this case insect larvae, have an odour which is characteristic for each species and specific for the environment in which they live. This is a very important parameter to consider when choosing the scent target to use for the training. Indeed, the saproxylophagous and xylophagous species, living inside wood mould or creating galleries in trunks, have a broad scent bouquet due to different sources of odours present in their habitat (e.g. fungi, sawdust and other organic materials) (
The method to train conservation dogs in finding live animals is similar to those used to find unanimated and non-biological targets and it is based on the positive reinforcement of the dog’s behaviour (
During the second phase of training, the scent discrimination phase, the dog learns to discriminate between the target odour and other scents by consolidating, at the same time, the search behaviour and the signalling display; this process is also called “generalisation” of an odour (
A dog can be trained to offer an active or passive response to the target odour (
Creating a cohesive and efficient dog-handler team is critical to the success of the work; the dog must be able to search, locate and signal the target, while the handler has to make this possible by managing the dog in the field and, at the same time, correctly interpreting the behaviour of the dog. It is important to recognise that the searching ability varies between different dog-handler teams (
Several authors suggest that the best parameters to describe the ability of conservation dogs in correctly locating their target are the overall percentage of correct indications and the percentage of correctly detected targets for the total number of targets (
In the majority of the previously listed cases, the average accuracy for conservation dogs was around 90%, although it was variable. Low accuracy may be caused by several factors, such as: age of the dog, insufficient training, problems in the dog-handler team communication, inexperience of the trainer and/or handler (
While working in the field, several sources of disturbance can further decrease the accuracy of the search: temperature, wind, fatigue and presence of wild animals, their traces or humans (
The breed of dog selected as a CDD suitable for searching O. eremita was the Golden Retriever, a breed widely used to search for biological targets. In fact, the olfactory capabilities of these dogs and their nature make them easy to train and to handle during fieldwork. The dog, which was named Teseo (Figure
The training was carried out in successive steps, as a function of the age of the dog and according to the level of skill (Table
Summary of the training progression of Teseo.
Dog age (months) | Location | Training | Rate |
---|---|---|---|
6–9 | Fenced training area and public parks | Basic obedience training Search games Agility activities |
2 to 3 times/week |
9–16 | Fenced area | Imprinting phase (target: living larvae) | 2 to 5 times/week |
16–24 | Natural areas Osmoderma-free | Discrimination phase (target: nitrocellulose filters with the smell of the target) Preliminary discrimination tests (target: living larvae of Oryctes nasicornis, Gnorimus variabilis) |
5 times/week |
During the early months of the dog’s life, preparatory activities for the next training steps were carried out: i) basic obedience training, in which the dog learned some basic commands (e.g. stay, come, sit etc.); ii) search games, i.e. hiding small toys or pieces of food and rewarding the dog with play and iii) agility activities, in order to improve the oral and gestural communication between the dog and handler. During this phase, 2 or 3 training sessions were performed each week in a fenced area. Each session lasted for no more than 2 hours with several breaks to avoid stressing the puppy.
From this phase onwards, the dog wore a harness when working (Figure
In the following phases, the larvae were placed inside perforated vials without washing in order to better protect them during the work (Figure
During every training day, 1 to 5 consecutive sessions were carried out with a single target hidden in a tree and this was repeated for 2 to 5 times a week. The number and the length of the daily working sessions were gradually increased as was the number of trees without the target. After 1 or 2 sessions, the dog was allowed to rest and to play for 5–15 minutes. The imprinting phase ended when the dog had learned to search and unambiguously signal the target.
During the discrimination phase, the training sessions were carried out as simulations of real fieldwork. The training was conducted in natural and semi-natural areas suitable for O. eremita (Table
Summary of the areas in the province of Rome (Latium, Italy) where the training and the accuracy tests were carried out. SA: sub-areas for training sessions; TREES: tree species present in the area and in which the target was hidden (Qi: Quercus ilex; Qs: Quercus suber; Pt: Populus tremula); TR: training areas; AC: accuracy test areas; Oasi = private Nature Reserve; PRU = Regional Urban Park; RN = Nature Reserve; Villa = city park with annexed historical buildings.
Area | SA | TREES | TR | AC |
---|---|---|---|---|
RN Monte Mario | 1 | Qi; Qs | x | x |
RN Monte Mario | 2 | Qi | x | |
Villa Doria Pamphilj | 1 | Qi; Qs | x | x |
Villa Doria Pamphilj | 2 | Qi; Qs | x | x |
Villa Doria Pamphilj | 3 | Qi | x | x |
Villa Doria Pamphilj | 4 | Qi; Qs | x | |
PRU del Pineto | 1 | Qs | x | x |
PRU del Pineto | 2 | Qs | x | x |
PRU del Pineto | 3 | Pt | x | |
RN Insugherata | 1 | Qi; Qs | x | |
Oasi LIPU Castel di Guido | 1 | Qi | x |
Small nitrocellulose filters were impregnated with the target odour by placing the larva in small containers, filled with filters for at least 8 hours. Filters, prepared in this way, can retain the target odour for a long period, if stored in hermetic containers. These filters are small and can be easily hidden in very small cavities and are thus invisible to the dog. These filters also allow the undertaking of long training sessions with multiple targets, simulating areas with a low or a high population density of O. eremita. A further important point in favour of the filters is the fact that the use of live larvae of the target species (i.e. a protected insect), can be substantially reduced. Disposable latex gloves and tweezers were used when handling filters to avoid transferring the target odour to the hands of the handler and field assistants.
In this phase, during each training session, 3 to 15 filters were hidden in randomly selected trees. To avoid the smell left behind by the trainer while placing the filters and which could influence the dog, all trees to be searched (those with and without target) had been touched by the trainer prior to the actual session. Only then was Teseo permitted to search one tree at a time, alternating between trees with and without targets (Figure
Tests were carried out to verify whether Teseo misidentified larvae of species closely related to O. eremita and potentially syntopic in natural habitats. Some preliminary tests were carried out using larvae of Oryctes (Oryctes) nasicornis (Linnaeus, 1758) (Coleoptera: Scarabaeidae: Dynastinae) and Gnorimus variabilis (Linnaeus, 1758) (Coleoptera: Scarabaeidae: Cetoniinae). In every test, one larva of O. eremita was presented with one of the other species listed above. The larvae were hidden in perforated boxes and randomly mixed with empty boxes. Each day, 2 to 4 tests were carried out with a 10 minutes’ break between two successive tests. The dog was rewarded only after signalling correctly.
Accuracy, sensitivity and specificity were calculated following
Definition and formulae to calculate Accuracy, Sensitivity and Specificity. CPS: correct positive signalling (total n° of targets present in trees and correctly detected and signalled by the dog); CNS: correct negative signalling (total n° of trees without target and not signalled); NT: total n° of trees investigated; TT: total n° of targets present in the trees; TND: target not detected (total n° of targets present in the trees and not detected); NR: no reaction; TWD: targets wrongly detected (total n° of trees without target signalled by the dog as if the target was present).
Accuracy | the overall proportion of correct indications (“the rate of correct classification”, Allouche 2006) | CPS+CNS/NT |
Sensitivity | the proportion of correct positive indications (“the probability that the model will correctly classify a presence”, Allouche 2006) | CPS/TT(CPS+TND) |
Specificity | the proportion of correct negative indications (“the probability that the model will correctly classify an absence”, Allouche, 2006) | CNS/NR(CNS+TWD) |
Areas (AREA) and sub-areas (SA) in the province of Rome where the accuracy tests with nitrocellulose filters were carried out. TREES: tree species where filters were hidden (Qi: Quercus ilex; Qs: Quercus suber); NT: total n°of trees investigated; TT: total number of targets. Indication by Teseo: NR: total n° of “no reaction”, recognised as “target not present”, PS: total n° of “partial signalling” recognised as “false signalling”, CS: total n° of “complete signalling” recognised as “target detected”; Results: CPS: total n° of correct positive signalling (total n° of target correctly detected by the dog), TND: total n° of not-detected targets, CNS: correct negative signalling (NR to a tree without target), TWD: target wrongly detected (wrong CS to a tree without target); ACC: accuracy (CPS+CNS/NT); SEN: sensitivity (CPS/CPS+TND); SPE: specificity (CNS/CNS+TWD).
Area | SA | TREES | NT | TT | NR | PS | CS | CPS | TND | CNS | TWD | ACC | SEN | SPE |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
RN Monte Mario | Qi; Qs | 49 | 6 | 44 | 3 | 5 | 4 | 2 | 42 | 1 | 93.87 | 66.66 | 97.67 | |
Villa Doria Pamphilj | 1 | Qi; Qs | 37 | 5 | 27 | 6 | 10 | 5 | 0 | 27 | 5 | 86.49 | 100 | 84.37 |
Villa Doria Pamphilj | 2 | Qi; Qs | 46 | 6 | 36 | 8 | 10 | 6 | 0 | 36 | 4 | 91.30 | 100 | 90.00 |
Villa Doria Pamphilj | 3 | Qi | 60 | 7 | 49 | 8 | 11 | 6 | 1 | 48 | 5 | 90.00 | 85.71 | 90.57 |
PRU del Pineto | 1 | Qs | 20 | 4 | 16 | 2 | 4 | 4 | 0 | 16 | 0 | 100 | 100 | 100 |
PRU del Pineto | 2 | Qs | 51 | 6 | 45 | 1 | 6 | 3 | 3 | 42 | 3 | 94.18 | 50.00 | 93.33 |
Mean | 92.64 | 83.73 | 92.66 |
Accuracy measurements in Forcella Buana (FB) and San Vito (SV) considering larvae and frass and remains of adults (F+R) as target. NT: total number of trees investigated; TT: total number of targets present in trees; L13 and L16: total number of trees colonised by larvae of O. eremita in 2013 and 2016 respectively; F+R: total number of trees in which frass (F) and/or remains of adults (R) were found in 2013 and 2016; NR: no reaction; PS: partial signalling; CS: complete signalling; CPS: correct positive signalling; TND target non-detected; CNS: correct negative signalling; TWD: target wrongly detected.
TT | Indications by Teseo | CPS | TND | CNS | TWD | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Area | NT | L13 | L16 | F+R | TOT | NR | PS | CS | L13 | L16 | F+R | TOT | L13 | L16 | F+R | TOT | ||
FB | 84 | 4 | 4 | 15 | 23 | 61 | 7 | 23 | 4 | 1 | 4 | 9 | 0 | 3 | 11 | 14 | 47 | 14 |
SV | 48 | 2 | 2 | 6 | 10 | 32 | 8 | 16 | 1 | 2 | 4 | 7 | 1 | 0 | 2 | 3 | 29 | 9 |
TOT | 132 | 6 | 6 | 21 | 33 | 93 | 15 | 39 | 5 | 3 | 8 | 16 | 1 | 3 | 13 | 17 | 76 | 23 |
The targets (filters with the target odour) were hidden by a field assistant unbeknown to dog and handler (double blind test) in randomly chosen trees. Before the search, the field assistant touched all trees to be searched to avoid providing olfactory help for the dog. During the search sessions, the handler reported to the field assistant the interpretation of the dog’s behaviour, distinguishing between: no reactions (NR, the dog showed no reactions indicating the target); complete signalling (CS, the dog pointed to the target, sat, barked and looked at the scent source and handler). Sometimes the dog performed partial signalling (PS, e.g. the dog did not sit or barked only weakly). In these cases, the handler recognised the reaction as “false signalling” (FS) and reported that the target was not present (considered as “NR”). All results were recorded in a field sheet (Figure
The accuracy of Teseo was also measured in two areas (San Vito and Forcella Buana) where the presence of O eremita had been ascertained in previous studies by wood mould sampling (
The CDD team: the dog, the handler and the field assistant ready for a working session (Photo by Emilia Capogna).
Session ID | Date | S/E Time | |||||
---|---|---|---|---|---|---|---|
Area | Operators | ||||||
Weather | T(i) | H(i) | W(i) | Notes | |||
T(f) | H(f) | W(f) | |||||
Dog indications | Results | ||||||
Tree ID | Trg | NR | PS | CS | TP | FS | Notes |
The overall accuracy, sensitivity and specificity (Table
The results of the evaluation of accuracy are summarised in Table
The efficiency of the dog-handler team in detecting O. eremita larvae inside trees in Forcella Buana and San Vito was compared with the efficiency of the wood mould sampling technique in the same areas. The average time spent in 2016 to investigate a single tree by the two methods was calculated as the proportion between the total amount of time spent in the field by all operators and the total number of trees investigated. Two operators were needed to work with the dog and two operators were also required for wood mould sampling for each tree.
At the end of the training period, Teseo was ready for the fieldwork; the dog was able to detect larvae of O. eremita and to signal the presence of its target inside trees by sitting down, barking and looking at the scent source and the handler (Figure
Teseo signalling the target to the handler: A sitting beside a tree containing the target, barking and looking at scent source and handler B pointing the target, barking and looking at the handler C scratching the trunk and barking (Photos A and B by Emilia Capogna, photo C by Sӧnke Hardersen).
Accuracy measurements in Forcella Buana (FB) and San Vito (SV) considering only larvae as target. NT: total number of trees investigated; TT: total number of target present in trees; L13 and L16: total number of trees colonised by larvae of O. eremita in 2013 and 2016 respectively; F+R: total number of trees in which frass (F) and/or remains of adults (R) were found in 2013 and 2016; NR: no reaction; PS: partial signalling; CS: complete signalling; CPS: correct positive signalling; TND targets non-detected; CNS: correct negative signalling; TWD: target wrongly detected.
TT | Indication by Teseo | CPS | TND | CNS | TWD | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Area | NT | L13 | L16 | TOT | NR | PS | CS | L13 | L16 | TOT | L13 | L16 | TOT | ||
FB | 84 | 4 | 4 | 8 | 61 | 7 | 23 | 4 | 1 | 5 | 0 | 3 | 3 | 58 | 18 |
SV | 48 | 2 | 2 | 4 | 32 | 8 | 16 | 1 | 2 | 3 | 1 | 0 | 1 | 31 | 13 |
TOT | 132 | 6 | 6 | 12 | 93 | 15 | 39 | 5 | 3 | 8 | 1 | 3 | 4 | 89 | 31 |
Accuracy measurement for larvae of flower chafers species. NT: total number of trees; TT: total number of targets. Indication by Teseo: NR: no reaction, PS: partial signalling, CS: complete signalling; Results: CPS: correct positive signalling, TND targets non-detected, CNS: correct negative signalling, TWD: target wrongly detected.
Area | NT | TT | NR | PS | CS | CPS | TND | CNS | TWD |
---|---|---|---|---|---|---|---|---|---|
Forcella Buana | 84 | 32 | 60 | 6 | 24 | 7 | 25 | 35 | 17 |
San Vito | 48 | 14 | 30 | 5 | 18 | 5 | 9 | 21 | 13 |
TOT | 132 | 46 | 90 | - | 42 | 12 | 34 | 56 | 30 |
The discrimination tests with larvae of Oryctes (Oryctes) nasicornis and Gnorimus variabilis showed similar results. Teseo correctly exclusively signalled the larvae of O. eremita and sometimes showed some faint reactions to the larvae of the other species (e.g. sitting beside the source of the odour or barking weakly). After 2 or 3 repetitions of the tests, Teseo showed no reactions to the larvae of O. nasicornis and G. variabilis. However, it was noticed that during a few of the training sessions following these discrimination tests, the dog committed a higher rate of errors. Nevertheless, after a few training sessions, Teseo recovered his usual level of accuracy. For this reason it was decided to stop these tests.
When working with nitrocellulose filters, Teseo showed an accuracy of 93%, a sensitivity of 84% and a specificity of 93% (Table
Summary of Teseo’s accuracy (ACC), sensitivity (SEN) and specificity (SPEC). Filters: the filters with odour of the larvae of O. eremita; L13, L16: larvae recorded in 2013 and 2016; F+R: frass and remains of adults; FC: larvae of flower chafers; FB: Forcella Buana; SV: San Vito.
Target | Area | Overall accuracy | Accuracy without handler correction | Handler contribution | |||||
---|---|---|---|---|---|---|---|---|---|
ACC (%) | SEN (%) | SPEC (%) | ACC (%) | SEN (%) | SPE (%) | ACC (%) | SPE (%) | ||
Filters | 92.64 | 83.73 | 92.66 | 80.81 | 83.73 | 80,07 | 11,83 | 12,59 | |
L13, L16, F+R | FB | 66.67 | 39.13 | 77.05 | 58.33 | 39.13 | 65.57 | - | - |
SV | 75.00 | 70.00 | 76.31 | 58.33 | 70.00 | 55.26 | - | - | |
Mean | 70.83 | 54.56 | 76.68 | 58.33 | 54.56 | 60.41 | 12.50 | 16.27 | |
L13, L16 | FB | 75.00 | 62.50 | 76.31 | 66.67 | 62.50 | 67.10 | - | - |
SV | 70.83 | 75.00 | 70.45 | 54.17 | 75.00 | 52.27 | - | - | |
Mean | 72.91 | 68.75 | 73.38 | 60.42 | 68.75 | 59.68 | 12.49 | 13.70 | |
FC | FB | - | 21.87 | - | - | - | - | - | - |
SV | - | 35.71 | - | - | - | - | - | - | |
Mean | - | 28.79 | - | - | - | - | - | - |
The total time spent by the two operators to investigate 149 trees by wood mould sampling amounted to 198 hours (11,880 minutes) (48 trees in 96 hours in San Vito and 101 trees in 138 hours in Forcella Buana). The total time spent by the two operators to investigate 132 trees with Teseo amounted to 855 minutes (48 trees in 376 minutes in San Vito and 84 trees in 479 minutes in Forcella Buana). The mean overall time spent by two operators per tree for wood mould sampling and with the dog amounted respectively to about 80 minutes and to 6 minutes and 50 seconds.
The protocol developed to train the conservation detection dog in the MIPP project was successful in teaching the dog the specific task required, i.e. to find larvae of the saproxylic beetle O. eremita living inside hollow trees. Therefore the results showed that this rare and elusive beetle can be monitored with the aid of a trained dog. These results are in line with research on other animal species living in wood or in burrows (
The highest values were obtained if only larvae were considered as the target (i.e. excluding frass and remains) (Table
Confirmation that the dog has been successfully imprinted is also provided by the results of the preliminary discrimination test and by the low sensitivity in signalling larvae of other flower chafers species which often share the same cavity with O. eremita. In particular, Teseo showed a much lower sensitivity to larvae of flower chafers (29%) when compared to the larvae of O. eremita (69%). This result is similar to
These results on accuracy and sensitivity of Teseo are consistent with those obtained in other studies involving dogs in the search for saproxylic beetles. For example, a sensitivity of 78% was obtained for dogs trained to find the red palm weevil, Rhynchophorus ferrugineus (
The difference between the values of accuracy measured with nitrocellulose filters and larvae may depend on several factors. In general, working in a natural setting with live targets is certainly more complicated than searching for filters placed by operators. Other studies have also shown that sensitivity was lower under realistic conditions (
A further important point to consider is which factors increase the level of fatigue in the dog and consequently decrease its reliability (e.g.
Precautions should be taken to minimise the effects of these factors, such as: i) carry out some preliminary surveys to allow the dog to become familiar with the working area; in fact, it is well known that accuracy measurements in new areas can initially be low and can increase in later surveys (
The lower accuracy measured on trees colonised by larvae of O. eremita may also depend on factors related to the detection probability (i.e. the probability to detect the larvae in a tree, if present) of the wood mould sampling method. In Forcella Buana and San Vito, results obtained by wood mould sampling were used to validate the accuracy, sensitivity and specificity of the signalling of Teseo. However,
Another very important factor to take into account is the relationship between the dog and the handler (cf.
The results of the tests carried out demonstrated that the use of the CDD was a better method to detect larvae of O. eremita when compared to WMS. In fact, the dog showed an overall probability of detecting colonised trees in the area of Forcella Buana and San Vito of 73%, that is higher than the detection probability with WMS (34–50%) in the same areas (
For the base training and the imprint phase, a 3m training leash was used. Subsequently, when the dog had learned to pay attention to the trainer when he was wearing the harness, no leash was used.
Similarly, the leash was used during the initial conditioning with the clicker: conditioning sessions, lasting 5 minutes, were carried out, giving the dog small pieces of tasty food (different to that used for rewarding the dog after correct signalling) as a reward simultaneously with the click. After the dog had well learned to associate the sound of the click with the food, daily sessions (up to 15 minutes) were carried out without the leash. Metallic clickers were preferable as they were more resistant and produce a louder sound. As a reward for a target detected successfully, small pieces of chicken sausage were used. Disposable latex gloves should be used when handling filters or larvae to avoid transferring the target odour to the hands of the trainer, which might confuse the dog.
To avoid interferences in the field during training or monitoring sessions:
• There should be as few people as possible and it would be preferable if the dog was familiar with all the people present.
• The field assistant must stay distant and out of the trajectory of the dog-handler team while working in order to avoid creating disturbance.
• If possible, working should be avoided during rainy and windy days.
• If it is necessary to work during periods with very high temperatures, the hottest hours of the day should be avoided and it is suggested that work should be undertaken early in the morning or late in the afternoon.
When trees are close to each other and in dense woods, it was observed that the dog can become confused as the target odour can apparently move from a source tree. In these cases, the dog can perceive the smell beside another tree and this effect is increased by the wind. When these conditions occur, it might be better to work on groups of trees rather than on individual trees.
It was noticed that Teseo performed better when carrying out a maximum of 5 training sessions per week, alternated with 2 days of rest. When the dog was fully trained (i.e. he reached the expected level of accuracy), the training rate could be reduced to 2 or 3 sessions per week (i.e. maintenance training). However, before working in the field, the rate of training should be increased again to 5 times per week. It would be necessary to start at least 6 weeks earlier and to gradually increase the following parameters: the number of weekly training sessions, the number of daily sessions, the number of trees examined (both with and without target) and the general complexity of the sessions. It is recommended to carry out some training sessions in which only one target is used (in the last tree surveyed during the session) in order to get the dog used to working in areas with low population density of the target species (or where the target species might not be present).
A conservation detection dog is a powerful tool for locating O. eremita and these results can be useful for the other related European species of Osmoderma (
We would like to thank the following people for help during fieldwork: Bianchi E., Capogna E., Cini A., Cuccurullo A., Frangioni F., Gallitelli L., Garzuglia F., Grant F., Khroa S., Mancini K., Mantoni C., Nigro G., Petruccelli L., Piermaria L., Redolfi De Zan L., Santoro R. We are grateful to Altea T., Romano M., Eusepi L., Desprini F., Filippone I. (Comando Unità Tutela Forestale Ambientale e Agroalimentare Carabinieri - CUTFAA, formerly CFS, Italian State Forestry Corps, local biodiversity office of Castel di Sangro), Quilghini G., Zoccola A., Marsella S., Rossi B., Bertinelli S. (CUTFAA, local biodiversity office of Pratovecchio), Febbo D., Sulli C., Tollis P. (Abruzzo, Lazio and Molise National Park, in particular), Fedrigoli L. and Mazzocchi F. (CUTFAA, local biodiversity office of Verona) for fieldwork and logistics. The MIPP staff is grateful to Di Marzio V., Tommasini Degna M. (Centro Veterinario Gregorio VII www.gregoriovii.com), Paoletti S., De Cato C., Gasparri S. (A.N.U.C.S.S. www.anucss.org) and to Hoyer-Tomiczek U. (Department of Forest Protection, BFW – Austrian Research Centre for Forests) and Sauseng G. We would like to thank Emilia Capogna for allowing us to use her photographs. Fabio and Teseo particularly like to thank Silvia, Gabriele and Valerio for their invaluable help for the physical and professional growth of Teseo.
The present work was developed within the EU project LIFE11 NAT/IT/000252, with the contribution of the LIFE financial instrument of the European Union.
With the contribution of the LIFE financial instrument of the European Union.