Abstract: Two experiments were conducted to study the effect of varying the temporal distrbution of conditioning sessions on equine learning behavior. In the first experiment, 15 ponies were trained to clear a small hurdle in response to a buzzer in order to avoid a mild electric shock. Three treatments were used. One group received 10 learning trials daily, seven times a week; one group was trained in the same fashion two times a week and one group was trained once a week. The animals conditioned only once a week achieved a high level of performance in significantly fewer sessions than the ones conditioned seven times a week, although elapsed time from start of training to completion was two to three times greater for the former group. The twice-a-week group learned at an intermediate rate. In the second experiment, the ponies were rearranged into three new groups. They were taught to move backward a specific distance in response to a visual cue in order to avoid an electric shock. Again, one group was trained seven times a week, one group was trained two times and one group was trained once a week. As in the first experiment, the animals trained once a week achieved the learning criteria in significantly fewer sessions than those trained seven times a week, but, as in trial 1, elapsed time from start to finish was greater for them. The two times-a-week group learned at a rate in-between the rates of the other two groups.

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.

Abstract: Two rhesus monkeys, given 60 two-hour sessions with a six-device mechanical puzzle showed clear evidence of learning, the curve showing ratio of incorrect to correct responses appearing quite comparable to similar curves obtained during externally rewarded situations. When, on the thirteenth day of tests, the subjects were presented with the puzzle 100 times at 6-minute intervals, the number of devices manipulated decreased regularly throughout the day, although there was no significant change in the number of times the problem assembly was attacked.

Abstract: This study explored the relationship between two creative styles (adaptor and innovator) and the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience). 164 teachers from 3 secondary and 2 primary schools in Singapore completed a self?report questionnaire, which consisted of the Kirton Adaption?Innovation Inventory and the NEO?Five Factor Inventory. It was found that adaptors were significantly more conscientious than innovators, while innovators were significantly more extraverted and open to experience than adaptors. No significant differences were found between adaptors and innovators in neuroticism and agreeableness. The study also revealed a meaningful pattern of relationships between the Big Five personality traits and the three facet scales of the KAI. Specifically, Sufficiency of Originality was negatively correlated with Openness to Experience and Extraversion; Rule Governance was positively correlated with conscientiousness but negatively correlated with openness to experience; Efficiency was positively correlated with conscientiousness. The overall findings supported the fundamental contention that different creative styles were due to different combinations of personality traits, with adaptors being more conscientious, while innovators being more extraverted and open to experience. These personality?based differences in creative styles between adaptors and innovators had resulted in much social conflict between them. One way of resolving it is to make known the nature and value of different creative styles to these two different types of creators.

Abstract: ABSTRACT For many ecosystems, feral horses are increasingly becoming an important if not dominant component of ungulate biomass and hence influence on community dynamics. Yet we still know little of how horses contribute to key ecological interactions including predator-prey and indirect competitive relationships at a community level. Notably, feral species like horses can exhibit life-history traits that differ from that of native (mainly artiodactyl) herbivore competitors. Artificial selection for traits like increased, early, or extended reproduction that have yet to be reversed by natural selection, coupled with naturally selected differences in anatomy and behavior, in addition to unique management objectives for horses compared to other species, means that the dynamics of feral horse populations are not likely to align with what might be expected of other large herbivores. Unexpected population dynamics and inherent biological asymmetries between native ungulates and feral horses may therefore influence the former via direct competition for shared resources and through enemy-mediated interactions like apparent competition. In several localities feral horses now co-exist with multiple native prey species, some of which are in decline or are species at risk. Compounding risks to native species from direct or indirect competitive exclusion by horses is the unique nature and socio-political context of feral horse management, which tends towards allowing horse populations to be limited largely by natural, density-dependent factors. We summarize the inherent asymmetries between feral horse biology and that of other ungulate prey species with consequences for conservation, focusing on predator-prey and emerging indirect interactions in multi-prey systems, and highlight future directions to address key knowledge gaps in our understanding of how feral horses may now be contributing to the (re)structuring of food webs. Observations of patterns of rapid growth and decline, and associated skews in sex ratios of feral horse populations, indicate a heightened potential for indirect interactions among large ungulate prey species, where there is a prevalence of feral horses as preferred prey, particularly where native prey are declining. In places like western North America, we expect predator-prey interactions involving feral horses to become an increasingly important factor in the conservation of wildlife. This applies not only to economically or culturally important game species but also at-risk species, both predators (e.g., wolves [Canis lupus], grizzly bears [Ursus arctos]) and prey (e.g., woodland caribou [Rangifer tarandus caribou]), necessitating an ecological understanding of the role of horses in natural environments that goes beyond that of population control. ? 2021 The Wildlife Society.