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Context. Continued miniaturisation of tracking technology increases its utility in animal applications. However, species morphology often dictates the type of animal-borne device (ABD) that can be used, and how it is attached. The morphology of species within Peramelemorphia preclude them from the standard collar attachment of ABDs for terrestrial mammals.
Aims. This paper describes a method for the tail-mount attachment of ABDs, and deployment results for Peramelemorphia across arid, semi-arid and temperate Australia to (a) test the performance of attachments and ABDs in the field and (b) discuss the animal welfare considerations for this attachment method.
Methods. Tail-mount attachment of ABDs were field-tested on a total of 80 greater bilbies (Macrotis lagotis), and 14 long-nosed bandicoots (Perameles nasuta).
Key results. Time to natural detachment (TTND) was between 2 and 52 days, with 65.74% (142 of 216) remaining on until manual removal. For ABDs that were manually removed, attachments were retained for up to 94 days. The method used for tail-mount attachment of ABDs to long-nosed bandicoots resulted in significantly shorter TTND compared with the method used for bilbies, and environmental factors (high temperatures and rainfall) had a negative effect on TTND. Tail-mount attached global positioning system (GPS) sensors collected large quantities of accurate data, with a maximum fix success rate of 83.38%. Damage to GPS (antenna breakage and water ingress) during deployment, however, impacted performance. In environments with frequent rainfall and waterlogged soils, the tape on a small proportion (6.25%) of (n = 192) attachments to bilbies caused tail injury. All injuries were resolvable, with most requiring minimal to no veterinary intervention.
Key conclusions. Attachment longevity can be affected by how the ABD is mounted to the tail, the species and the deployment environment. The environment can also affect which adhesive tapes are suitable for ABD attachment. However, this method is highly modifiable, practical for field application and can have long retention times relative to other temporary methods.
Implications. This ABD tail-mount attachment method adds another tool to the telemetry tool-kit, with all the benefits of a low-tech, low-cost, passive drop-off type attachment. This method has demonstrated practicality for Peramelemorphia, with potential application to other suitable small vertebrates.
Context. The wide-ranging movement of African elephants (Loxodonta africana) is largely driven by the spatio-temporal distribution of water and forage, and often leads to their travelling outside of formally protected areas. With an increase in drier periods predicted across Africa due to climate change, it is critically important to understand how elephants physiologically respond to alterations in the availability and distribution of resources.
Aims. We assessed variation in the adrenal activity of elephants living in Kenya’s Tsavo East National Park between wet and dry seasons, as well as among individuals found in Tsavo East National Park and privately protected Rukinga Wildlife Sanctuary (part of the Kasigau REDD+ wildlife corridor) in the dry season, when the area experiences an influx of elephants in search of alternative resources.
Methods. We opportunistically collected fresh elephant faecal samples across the two seasons and locations for analysis of faecal glucocorticoid metabolite (fGCM, a proxy for stress) and nitrogen (Nf, an indirect measure of diet quality) concentrations. The Normalised Difference Vegetation Index (NDVI) was employed as an additional indicator of habitat quality.
Key results. In Tsavo East N.P. Nf and NDVI were both significantly lower during the dry season, indicating poorer habitat quality compared with the wet season. Although elephant fGCM concentrations tended to be higher in the dry season than the wet, the differences were not significant. There was no difference between elephant fGCMs measured in Tsavo East N.P. and Rukinga W.S. during the dry season, nor in habitat quality between the two locations.
Conclusions. Elephants living in Tsavo may be physiologically unaffected by (or adapt to) typical seasonal changes in habitat quality that could lead to nutritional stress; however, whether this is the case during extended periods of severe drought requires further investigation. Rukinga W.S. provides a safe haven of sufficient habitat quality for elephants searching for alternative resources during this period.
Implications. Extended dry periods are likely to become increasingly common in semiarid savannahs, and implications for wildlife must be closely monitored. Privately protected land outside formally protected areas plays an important role in conservation efforts, which should be considered when making land management plans.
Context. Vehicle collisions with wildlife can injure or kill animals, threaten human safety, and threaten the viability of rare species. This has led to a focus in road-ecology research on identifying the key predictors of ‘road-kill’ risk, with the goal of guiding management to mitigate its impact. However, because of the complex and context-dependent nature of the causes of risk exposure, modelling road-kill data in ways that yield consistent recommendations has proven challenging.
Aim. Here we used a multi-model machine-learning approach to identify the spatio-temporal predictors, such as traffic volume, road shape, surrounding vegetation and distance to human settlements, associated with road-kill risk.
Methods. We collected data on the location, identity and wildlife body size of each road mortality across four seasons along eight roads in southern Tasmania, a ‘road-kill hotspot’ of management concern. We focused on three large-bodied and frequently affected crepuscular Australian marsupial herbivore species, the rufous-bellied pademelon (Thylogale billardierii), Bennett’s wallaby (Macropus rufogriseus) and the bare-nosed wombat (Vombatus ursinus). We fit the point-location data using ‘lasso-regularisation’ of a logistic generalised linear model (LL-GLM) and out-of-bag optimisation of a decision-tree-based ‘random forests’ (RF) algorithm for optimised predictions.
Results. The RF model, with high-level feature interactions, yielded superior out-of-sample prediction results to the linear additive model, with a RF classification accuracy of 84.8% for the 871 road-kill observations and a true skill statistic of 0.708, compared with 61.2% and 0.205 for the LL-GLM. The lasso rejected road visibility and human density, ranking roadside vegetation type and presence of barrier fencing as the most influential predictors of road-kill locality.
Conclusions. Forested areas with no roadside barrier fence along curved sections of road posed the highest risk to animals. Seasonally, the frequency of wildlife–vehicle collisions increased notably for females during oestrus, when they were more dispersive and so had a higher encounter rate with roads.
Implications. These findings illustrate the value of using a combination of attributive and predictive modelling using machine learning to rank and interpret a complexity of possible predictors of road-kill risk, as well as offering a guide to practical management interventions that can mitigate road-related hazards.
Brad Law, Leroy Gonsalves, Joanna Burgar, Traecey Brassil, Isobel Kerr, Lachlan Wilmott, Kylie Madden, Martin Smith, Valentina Mella, Mathew Crowther, Mark Krockenberger, Adrian Rus, Rod Pietsch, Anthony Truskinger, Phil Eichinski, Paul Roe
Context. It is notoriously difficult to estimate the size of animal populations, especially for cryptic or threatened species that occur in low numbers. Recent advances with acoustic sensors make the detection of animal populations cost effective when coupled with software that can recognise species-specific calls.
Aims. We assess the potential for acoustic sensors to estimate koala, Phascolarctos cinereus, density, when individuals are not identified, using spatial count models. Sites were selected where previous independent estimates of density were available.
Methods. We established acoustic arrays at each of five sites representing different environments and densities of koalas in New South Wales. To assess reliability, we compared male koala density estimates derived from spatial count modelling to independently derived estimates for each site.
Key results. A total 11 312 koala bellows were verified across our five arrays. Koalas were detected at most of our sample locations (96–100% of sensors; n = 130), compared with low detection rates from rapid scat searches at trees near each sensor (scats at <2% of trees searched, n = 889, except one site where scats were present at 69% of trees, n = 129). Independent estimates of koala density at our study areas varied from a minimum of 0.02 male koalas ha−1 to 0.32 ha−1. Acoustic arrays and the spatial count method yielded plausible estimates of male koala density, which, when converted to total koalas (assuming 1:1 sex ratio), were mostly equivalent to independent estimates previously derived for each site. The greatest discrepancy occurred where the acoustic estimate was larger (although within the bounds of uncertainty) than the independent mark–recapture estimate at a fragmented, high koala-density site.
Conclusions. Spatial count modelling of acoustic data from arrays provides plausible and reliable estimates of koala density and, importantly, associated measures of uncertainty as well as an ability to model spatial variations in density across an array. Caution is needed when applying models to higher-density populations where home ranges overlap extensively and calls are evenly spread across the array.
Implications. The results add to the opportunities of acoustic methods for wildlife, especially where monitoring of density requires cost-effective repeat surveys.
Context. Scarcity of standardised data is one of the main obstacles in understanding the responses of wildlife to anthropogenic pressures. By assessing local people’s knowledge, it is possible to generate valuable social-ecological data to fill this gap cost-effectively.
Aims. We present the Wildlife–Human Survey (WHS), a protocol for rapidly assessing information on medium and large-sized mammals, rural people, and the latter’s interactions with these species. In a pilot study, we investigate the effectiveness of our tool to generate valuable information for wildlife research and management.
Methods. The survey consists of a structured interview protocol that can be used as a tool to generate information on (i) the occurrence and assemblage composition of medium and large mammalian species, (ii) the socioeconomic profile of rural populations and farming activities in the area, and (iii) people’s perception of human–wildlife interactions (e.g. benefits, economic losses). To test the effectiveness of our tool, we conducted a total of 300 face-to-face interviews using this protocol in 30 rural landscapes (1250 ha each) in the Paraiba Valley region, São Paulo State, Brazil. We analysed the resulting data using descriptive statistics, random curves of species accumulation and maps of species distribution and richness.
Key results. We generated data on the occurrence and distribution of 32 species of medium and large mammals and on socioeconomic profile of the 300 surveyed households. We found that 95% of the species could be determined to occur in the region, with an effort ranging from 66 to 266 h; up to 611 h were necessary to find evidence of all species.
Conclusions. Our protocol can be an effective, fast and low-cost tool for appraising the occurrence of medium and large-sized mammals, the socioeconomic profile of people sharing rural landscapes with them and their interactions.
Implications. The WHS can generate information for mammal management by highlighting hotspot areas of human–wildlife interactions. This protocol can be especially useful when and where other methods are inadequate/unviable, and create the opportunity for rural people to contribute to wildlife management by allowing them to share their knowledge and concerns about their interactions with the local fauna.
Context. Destruction of rabbit warrens to prevent re-invasion is an important component of integrated rabbit management. Ripping, and less commonly blasting with explosives, are used to destroy warren systems and to kill any rabbits remaining in warrens, usually after the population has already been reduced. However, the use of these methods can sometimes be constrained by vegetation, topography, presence of culturally significant sites or important habitats, or they may be inefficient or expensive due to the low density of warrens. Gas explosive devices provide an alternative method in these situations; however, little is known about their animal welfare impacts. The R3 Unit is a gas explosive device used in Australia. It pumps a calibrated mixture of propane and oxygen into a warren and then ignites the mixture, causing a blast wave to travel through the warren.
Aims. To determine the animal welfare impacts of the R3 Unit gas explosive device and to assess its effectiveness at achieving a rapid death in wild rabbits.
Methods. Trials of the R3 Unit were initially conducted in artificial warrens to determine the relationship between blast pressure, warren size and structure. We then assessed the extent of injury and probability of death of rabbits in both artificial and natural warrens.
Key results. As blast pressure increases within a warren, probability of death also increases. Blast pressures exceeding 56 psi will render rabbits unconscious, but a blast pressure of at least 67 psi is required to kill rabbits quickly and humanely. Sublethal blasts at lower pressures result in significant injuries that lead to severe suffering.
Conclusions. The R3 Unit can humanely kill rabbits when the blast pressure is sufficient to cause immediate unconsciousness and death (without regaining consciousness). To achieve adequate blast pressure, warrens must be small, with a diameter no more than 4 m, and all entrances must be sealed.
Implications. The R3 Unit can provide an effective alternative to warren ripping and blasting in certain situations. However, to ensure the device is used correctly to minimise animal welfare impacts, operators must be trained in its use and follow best practice procedures.
Context. The spatio-temporal partitioning of large carnivores is influenced by interspecific competition and coexistence within small, enclosed reserves. Lions (Panthera leo), spotted hyaenas (Crocuta crocuta) and leopards (Panthera pardus) are the three largest African carnivores and have the greatest potential for intra-guild competition, particularly where space is limited.
Aim. To investigate the spatio-temporal partitioning between lions, spotted hyaenas and leopards in a small (~75 000 ha), enclosed nature reserve, Madikwe Game Reserve (Madikwe), South Africa.
Methods. We deployed 110 camera traps (baited n = 55 and unbaited n = 55) across Madikwe from 26 August 2019 until 6 May 2020. Von Mises kernel density plots were used to investigate daily temporal partitioning among the three species. A multiple-species, single-season occupancy model was used to investigate daily space use patterns.
Key results. We found both temporal and spatial exclusion between lions and spotted hyaenas on Madikwe. However, no evidence was found of spatio-temporal partitioning between lions and leopards, and spotted hyaenas and leopards.
Conclusions. Exploitative and interference competition on Madikwe might be high enough to warrant spatio-temporal partitioning between lions and spotted hyaenas to avoid the negative effects of intra-guild competition. Contrastingly, patterns observed between leopards and both lions and spotted hyaenas preclude the possibility of top-down control by superior carnivores.
Implication. These findings call for an adaptive management approach, where both carnivore and prey species compositions are constantly monitored. Management strategies such as these will allow for the conservation of valuable resources (i.e. prey species) to ensure the persistence of large carnivore populations across African ecosystems.
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