In implicit learning, human subjects are exposed to patterned information, but they are not informed about the pattern. Typically, they demonstrate learning of that pattern, but little awareness of the experimental contingencies. In a nonhuman analog of this procedure, two cotton-top tamarins (Saguinus oedipus) were presented with a five-element chain that consisted of the same icon presented serially at different locations on a touchscreen. The tamarins had to touch the icon at each location to advance the chain and receive reinforcement at the end of the chain. One element of the chain was never differentially reinforced in the presence of another element, as is typically done in transitive inference and serial chaining studies. Following training, the tamarins were tested for their knowledge of the chain using pairwise tests that are common in transitive inference and serial chaining experiments, and a random test, common in some types of implicit learning, in which the sequence of elements was randomized. The results of both tests revealed that the tamarins appreciated the ordinal position of the elements composing the chain, although reinforcement had not been dependent on that knowledge.
This experiment examined the performance of common marmosets (Callithrix jacchus) on a series of patterned string problems to assess the marmosets’ understanding of means-ends relationships. One marmoset, Jet, was exposed to a series of problems that were ordered in terms of perceived difficulty during two testings that were separated by one year. In the second testing Jet received problems that had been used during the first testing along with three new problems. Each of the new problems was designed to be an exemplar of the type of problem that Jet had experienced difficulty with in the first testing. A second marmoset, Peaches, was tested on the same set of problems given to Jet in the second testing. Results indicated that the marmosets’ performance on these problems fell into three categories. In one category, some problems were solved without evidence of trial and error learning. In a second category, there were problems in which the marmosets responded at chance levels initially but evidenced improvement as a function of extended testing. In a third category, some problems appeared to be virtually unsolvable even with extended testing. Taken together, these results indicate that the marmosets were able to learn the means-ends connection between pulling a string and obtaining food. This learning was best characterized as a trial and error process for some problem forms, while for others there appeared to be rapid learning that did not require extensive practice. The instances of rapid learning may be the result of the application of a simple spatial proximity rule in which the marmosets chose the string that was closest to an imaginary line drawn between the marmoset and the reinforcer.
Global climate change has affected forest health and productivity. A highly visible, direct climate impact is dieback caused by drought periods in moisture-limited forest ecosystems. Here, we have used a climate moisture index (CMI), which has been developed in order to map forest–grassland transitions, to investigate the shifts of the zero-CMI isopleths, in order to infer drought vulnerabilities. Our main objective was to identify populations of the 24 most common western North American forest tree species that are most exposed to drought conditions by using a western North American forest inventory database with 55,700 plot locations. We have found that climate change projections primarily increase the water deficits for tree populations that are already in vulnerable positions. In order to test the realism of this vulnerability assessment, we have compared the observed population dieback with changes in index values between the 1961–1990 reference period and a recent 1991–2020 average. The drought impacts that were predicted by negative CMI values largely conformed to the observed dieback in Pinus edulis, Populus tremuloides, and Pinus ponderosa. However, there was one notable counter-example. The observed dieback in the Canadian populations of Populus tremuloides were not associated with directional trends in the drought index values but were instead caused by a rare extreme drought event that was not apparently linked to directional climate change. Nevertheless, a macro-climatic drought index approach appeared to be generally suitable to identify and forecast the drought threats to the tree populations.
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