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Broekhuis, F., Madsen, E. K., & Klaassen, B. (2019). Predators and pastoralists: how anthropogenic pressures inside wildlife areas influence carnivore space use and movement behaviour. Anim Conserv, .
Abstract: Abstract Across the globe, wildlife populations and their behaviours are negatively impacted by people. Protected areas are believed to be an antidote to increasing human pressures but even they are not immune to the impact of anthropogenic activities. Areas that have been set aside for the protection of wildlife therefore warrant more attention when investigating the impact of anthropogenic pressures on wildlife. We use cheetahs Acinonyx jubatus as a case study to explore how a large carnivore responds to anthropogenic pressures inside wildlife areas. Using GPS-collar data we investigate cheetah space use, both when moving and stationary, and movement parameters (speed and turn angles) in relation to human disturbance, distance to human settlement, livestock abundance and livestock site use inside wildlife areas. Space use was negatively influenced by human disturbance, resulting in habitat loss and fragmentation and potentially reducing landscape permeability between neighbouring wildlife areas. Cheetahs were also less likely to stop in areas where livestock numbers were high, but more likely to stop in areas that were frequently used by livestock. The latter could reflect that cheetahs are attracted to livestock however, cheetahs in the study area rarely predated on livestock. It is therefore more likely that areas that are frequently used by livestock attract wild herbivores, which in turn could influence cheetah space use. We did not find any effects of people and livestock on cheetahs? speed and turn angles which might be related to the resolution of the data. We found that cheetahs are sensitive to human pressures and we believe that they could be an indicator species for other large carnivores facing similar challenges. We suggest that further research is needed to determine the levels of anthropogenic pressures needed to maintain ecological integrity, especially inside wildlife areas.
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Burton, A. C., Neilson, E., Moreira, D., Ladle, A., Steenweg, R., Fisher, J. T., et al. (2015). REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes. J Appl Ecol, 52(3), 675–685.
Abstract: Summary Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial, and the suitability of alternatives such as occupancy estimation is debatable. We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology. Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence?absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions. Most studies estimating density used capture?recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site) or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement). Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technology's promise, but call for more explicit consideration of underlying processes of animal abundance, movement and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.
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Strien, A. J., Swaay, C. A. M., & Termaat, T. (2013). Opportunistic citizen science data of animal species produce reliable estimates of distribution trends if analysed with occupancy models. J Appl Ecol, 50(6), 1450–1458.
Abstract: Summary Many publications documenting large-scale trends in the distribution of species make use of opportunistic citizen data, that is, observations of species collected without standardized field protocol and without explicit sampling design. It is a challenge to achieve reliable estimates of distribution trends from them, because opportunistic citizen science data may suffer from changes in field efforts over time (observation bias), from incomplete and selective recording by observers (reporting bias) and from geographical bias. These, in addition to detection bias, may lead to spurious trends. We investigated whether occupancy models can correct for the observation, reporting and detection biases in opportunistic data. Occupancy models use detection/nondetection data and yield estimates of the percentage of occupied sites (occupancy) per year. These models take the imperfect detection of species into account. By correcting for detection bias, they may simultaneously correct for observation and reporting bias as well. We compared trends in occupancy (or distribution) of butterfly and dragonfly species derived from opportunistic data with those derived from standardized monitoring data. All data came from the same grid squares and years, in order to avoid any geographical bias in this comparison. Distribution trends in opportunistic and monitoring data were well-matched. Strong trends observed in monitoring data were rarely missed in opportunistic data. Synthesis and applications. Opportunistic data can be used for monitoring purposes if occupancy models are used for analysis. Occupancy models are able to control for the common biases encountered with opportunistic data, enabling species trends to be monitored for species groups and regions where it is not feasible to collect standardized data on a large scale. Opportunistic data may thus become an important source of information to track distribution trends in many groups of species.
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Harris, F. (1978). On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform. Proc IEEE, 66.
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Tebbich Sabine, Griffin Andrea S., Peschl Markus F., & Sterelny Kim. (2016). From mechanisms to function: an integrated framework of animal innovation. Philos Trans R Soc Lond B Biol Sci, 371(1690), 20150195.
Abstract: Animal innovations range from the discovery of novel food types to the invention of completely novel behaviours. Innovations can give access to new opportunities, and thus enable innovating agents to invade and create novel niches. This in turn can pave the way for morphological adaptation and adaptive radiation. The mechanisms that make innovations possible are probably as diverse as the innovations themselves. So too are their evolutionary consequences. Perhaps because of this diversity, we lack a unifying framework that links mechanism to function. We propose a framework for animal innovation that describes the interactions between mechanism, fitness benefit and evolutionary significance, and which suggests an expanded range of experimental approaches. In doing so, we split innovation into factors (components and phases) that can be manipulated systematically, and which can be investigated both experimentally and with correlational studies. We apply this framework to a selection of cases, showing how it helps us ask more precise questions and design more revealing experiments.
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Mann Janet, & Patterson Eric M. (2013). Tool use by aquatic animals. Phil. Trans. Biol. Sci., 368(1630), 20120424.
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Thornton Alex, & Lukas Dieter. (2012). Individual variation in cognitive performance: developmental and evolutionary perspectives. Philos Trans R Soc Lond B Biol Sci, 367(1603), 2773–2783.
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Van Schaik, C. P., & Burkart, J. M. (2011). Social learning and evolution: the cultural intelligence hypothesis. Philos Trans R Soc B, 366.
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Emery, N. J., Clayton, N. S., & Frith, C. D. (2007). Introduction. Social intelligence: from brain to culture. Philos Trans R Soc B, 362.
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Benson-Amram, S., & Holekamp, K. E. (2012). Innovative problem solving by wild spotted hyenas. Proc R Soc B, 279, 4087–4095.
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