| Records |
| Author |
Wasser, S.K.; Keim, J.L.; Taper, M.L.; Lele, S.R. |
| Title |
The influences of wolf predation, habitat loss, and human activity on caribou and moose in the Alberta oil sands |
Type |
Journal Article |
| Year |
2011 |
Publication |
Frontiers in Ecology and the Environment |
Abbreviated Journal |
Frontiers in Ecology and the Environment |
| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
Woodland caribou (Rangifer tarandus caribou) and moose (Alces alces) populations in the Alberta oil sands region of western Canada are influenced by wolf (Canis lupus) predation, habitat degradation and loss, and anthropogenic activities. Trained domestic dogs were used to locate scat from caribou, moose, and wolves during winter surges in petroleum development. Evidence obtained from collected scat was then used to estimate resource selection, measure physiological stress, and provide individual genetic identification for precise mark–recapture abundance estimates of caribou, moose, and wolves. Strong impacts of human activity were indicated by changes in resource selection and in stress and nutrition hormone levels as human-use measures were added to base resource selection models (including ecological variables, provincial highways, and pre-existing linear features with no human activity) for caribou. Wolf predation and resource selection so heavily targeted deer (Odocoileus virginiana or O hemionus) that wolves appeared drawn away from prime caribou habitat. None of the three examined species showed a significant population change over 4 years. However, caribou population estimates were more than double those of previous approximations for this area. Our findings suggest that modifying landscape-level human-use patterns may be more effective at managing this ecosystem than intentional removal of wolves. |
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Publisher  |
Ecological Society of America |
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Edition |
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| ISSN |
1540-9295 |
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| Notes |
doi: 10.1890/100071 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
5397 |
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| Author |
Amodio, P.; Boeckle, M.; Schnell, A.K.; Ostojic, L.; Fiorito, G.; Clayton, N.S. |
| Title |
Grow Smart and Die Young: Why Did Cephalopods Evolve Intelligence? |
Type |
Journal Article |
| Year |
2018 |
Publication |
Trends in Ecology & Evolution |
Abbreviated Journal |
Trends. Ecol. Evol. |
| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
Intelligence in large-brained vertebrates might have evolved through independent, yet similar processes based on comparable socioecological pressures and slow life histories. This convergent evolutionary route, however, cannot explain why cephalopods developed large brains and flexible behavioural repertoires: cephalopods have fast life histories and live in simple social environments. Here, we suggest that the loss of the external shell in cephalopods (i) caused a dramatic increase in predatory pressure, which in turn prevented the emergence of slow life histories, and (ii) allowed the exploitation of novel challenging niches, thus favouring the emergence of intelligence. By highlighting convergent and divergent aspects between cephalopods and large-brained vertebrates we illustrate how the evolution of intelligence might not be constrained to a single evolutionary route. |
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| Publisher |
Elsevier |
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Edition |
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| ISSN |
0169-5347 |
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| Notes |
doi: 10.1016/j.tree.2018.10.010 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
6508 |
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| Author |
Strien, A.J.; Swaay, C.A.M.; Termaat, T. |
| Title |
Opportunistic citizen science data of animal species produce reliable estimates of distribution trends if analysed with occupancy models |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Applied Ecology |
Abbreviated Journal |
J Appl Ecol |
| Volume |
50 |
Issue |
6 |
Pages |
1450-1458 |
| Keywords |
Bayesian inference; citizen science; detection; distribution; hierarchical modelling; Jags; monitoring; site occupancy |
| 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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| Publisher |
John Wiley & Sons, Ltd |
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Edition |
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| ISSN |
0021-8901 |
ISBN |
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| Notes |
doi: 10.1111/1365-2664.12158 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
6437 |
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| Author |
Hofmeester, T.R.; Cromsigt, J.P.G.M.; Odden, J.; Andrén, H.; Kindberg, J.; Linnell, J.D.C. |
| Title |
Framing pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi-species comparison |
Type |
Journal Article |
| Year |
2019 |
Publication |
Ecology and Evolution |
Abbreviated Journal |
Ecol Evol |
| Volume |
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Issue |
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Pages |
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| Keywords |
animal characteristics; detectability; environmental variables; mammal monitoring; reuse of data; trail camera |
| Abstract |
Abstract Obtaining reliable species observations is of great importance in animal ecology and wildlife conservation. An increasing number of studies use camera traps (CTs) to study wildlife communities, and an increasing effort is made to make better use and reuse of the large amounts of data that are produced. It is in these circumstances that it becomes paramount to correct for the species- and study-specific variation in imperfect detection within CTs. We reviewed the literature and used our own experience to compile a list of factors that affect CT detection of animals. We did this within a conceptual framework of six distinct scales separating out the influences of (a) animal characteristics, (b) CT specifications, (c) CT set-up protocols, and (d) environmental variables. We identified 40 factors that can potentially influence the detection of animals by CTs at these six scales. Many of these factors were related to only a few overarching parameters. Most of the animal characteristics scale with body mass and diet type, and most environmental characteristics differ with season or latitude such that remote sensing products like NDVI could be used as a proxy index to capture this variation. Factors that influence detection at the microsite and camera scales are probably the most important in determining CT detection of animals. The type of study and specific research question will determine which factors should be corrected. Corrections can be done by directly adjusting the CT metric of interest or by using covariates in a statistical framework. Our conceptual framework can be used to design better CT studies and help when analyzing CT data. Furthermore, it provides an overview of which factors should be reported in CT studies to make them repeatable, comparable, and their data reusable. This should greatly improve the possibilities for global scale analyses of (reused) CT data. |
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| Publisher |
John Wiley & Sons, Ltd |
Place of Publication |
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Series Issue |
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Edition |
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| ISSN |
2045-7758 |
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Conference |
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| Notes |
doi: 10.1002/ece3.4878 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
6518 |
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| Author |
Burton, A.C.; Neilson, E.; Moreira, D.; Ladle, A.; Steenweg, R.; Fisher, J.T.; Bayne, E.; Boutin, S. |
| Title |
REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes |
Type |
Journal Article |
| Year |
2015 |
Publication |
Journal of Applied Ecology |
Abbreviated Journal |
J Appl Ecol |
| Volume |
52 |
Issue |
3 |
Pages |
675-685 |
| Keywords |
animal movement; camera trap; capture-recapture; density estimation; imperfect detection; mammal monitoring; occupancy model; relative abundance; sampling error; wildlife survey methodology |
| 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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John Wiley & Sons, Ltd |
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0021-8901 |
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| Notes |
https://doi.org/10.1111/1365-2664.12432 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
6703 |
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| Author |
Karenina, K.; Giljov, A.; Ingram, J.; Rowntree, V.J.; Malashichev, Y. |
| Title |
Lateralization of mother�infant interactions in a diverse range of mammal species |
Type |
Journal Article |
| Year |
2017 |
Publication |
Nature Ecology & Evolution |
Abbreviated Journal |
Nat Ecol Evol |
| Volume |
1 |
Issue |
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Pages |
0030 Ep - |
| Keywords |
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| Abstract |
Left-cradling bias is a distinctive feature of maternal behaviour in humans and great apes, but its evolutionary origin remains unknown. In 11 species of marine and terrestrial mammal, we demonstrate consistent patterns of lateralization in mother�infant interactions, indicating right hemisphere dominance for social processing. In providing clear evidence that lateralized positioning is beneficial in mother�infant interactions, our results illustrate a significant impact of lateralization on individual fitness. |
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Nature Publishing Group SN - |
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no |
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Equine Behaviour @ team @ |
Serial |
6040 |
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| Author |
Boitani, L. |
| Title |
Patterns of homesites attendance in two Minnesota wolf packs |
Type |
Book Chapter |
| Year |
1982 |
Publication |
Wolves of the World: Perspectives of Behavior, Ecology and Conservation |
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| Publisher |
Noyes, Park Ridge |
Place of Publication |
New York |
Editor |
Harrington, F.H.; Paquet, P.C. |
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no |
| Call Number |
Equine Behaviour @ team @ Boitani1982 |
Serial |
6474 |
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| Author |
Eagle, N.; Pentland, A. |
| Title |
Eigenbehaviors: identifying structure in routine |
Type |
Journal Article |
| Year |
2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
| Volume |
63 |
Issue |
7 |
Pages |
1057-1066-1066 |
| Keywords |
Biomedical and Life Sciences |
| Abstract |
Longitudinal behavioral data generally contains a significant amount of structure. In this work, we identify the structure inherent in daily behavior with models that can accurately analyze, predict, and cluster multimodal data from individuals and communities within the social network of a population. We represent this behavioral structure by the principal components of the complete behavioral dataset, a set of characteristic vectors we have termed eigenbehaviors. In our model, an individual’s behavior over a specific day can be approximated by a weighted sum of his or her primary eigenbehaviors. When these weights are calculated halfway through a day, they can be used to predict the day’s remaining behaviors with 79% accuracy for our test subjects. Additionally, we demonstrate the potential for this dimensionality reduction technique to infer community affiliations within the subjects’ social network by clustering individuals into a behavior space spanned by a set of their aggregate eigenbehaviors. These behavior spaces make it possible to determine the behavioral similarity between both individuals and groups, enabling 96% classification accuracy of community affiliations within the population-level social network. Additionally, the distance between individuals in the behavior space can be used as an estimate for relational ties such as friendship, suggesting strong behavioral homophily amongst the subjects. This approach capitalizes on the large amount of rich data previously captured during the Reality Mining study from mobile phones continuously logging location, proximate phones, and communication of 100 subjects at MIT over the course of 9 months. As wearable sensors continue to generate these types of rich, longitudinal datasets, dimensionality reduction techniques such as eigenbehaviors will play an increasingly important role in behavioral research. |
| Address |
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| Publisher |
Springer Berlin / Heidelberg |
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Series Issue |
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Edition |
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| ISSN |
0340-5443 |
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Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
5189 |
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| Author |
Fischhoff, I.; Dushoff, J.; Sundaresan, S.; Cordingley, J.; Rubenstein, D. |
| Title |
Reproductive status influences group size and persistence of bonds in male plains zebra (Equus burchelli) |
Type |
Journal Article |
| Year |
2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
| Volume |
63 |
Issue |
7 |
Pages |
1035-1043-1043 |
| Keywords |
Biomedical and Life Sciences |
| Abstract |
Animal groups arise from individuals’ choices about the number, characteristics, and identity of associates. Individuals make these choices to gain benefits from their associations. As the needs of an individual change with its phenotype, so too we expect the nature of its associations to vary. In this paper, we investigate how the social priorities of male plains zebra (Equus burchelli) depend on reproductive state. An adult male is either a bachelor, and lacking mating access, or a stallion defending a harem. Multiple harems and bachelor males aggregate in larger herds. Herds frequently split and merge, affording males opportunities to change associates. Over a 4-year period, we sampled the herd associations in a population of 500–700 zebras. To isolate the effects of reproductive state on male social behavior, we account for potential confounding factors: changes in population size, grouping tendencies, and sampling intensity. We develop a generally applicable permutation procedure, which allows us to test the null hypothesis that social behavior is independent of male status. Averaging over all individuals in the population, we find that a typical bachelor is found in herds containing significantly more adults, bachelors, and stallions than the herds of a typical stallion. Further, bachelors’ bonds with each other are more persistent over time than those among stallions. These results suggest that bachelors form cohesive cliques, in which we may expect cooperative behaviors to develop. Stallion–stallion associations are more diffuse, and less conducive to long-term cooperation. |
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Springer Berlin / Heidelberg |
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0340-5443 |
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Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
5193 |
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| Author |
Franks, D.; James, R.; Noble, J.; Ruxton, G. |
| Title |
A foundation for developing a methodology for social network sampling |
Type |
Journal Article |
| Year |
2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
| Volume |
63 |
Issue |
7 |
Pages |
1079-1088-1088 |
| Keywords |
Biomedical and Life Sciences |
| Abstract |
Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network. |
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Springer Berlin / Heidelberg |
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0340-5443 |
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no |
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Equine Behaviour @ team @ |
Serial |
5194 |
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