Search results for "LEARNING"
showing 10 items of 6669 documents
Experimental evidence suggests that specular reflectance and glossy appearance help amplify warning signals
2017
AbstractSpecular reflection appears as a bright spot or highlight on any smooth glossy convex surface and is caused by a near mirror-like reflectance off the surface. Convex shapes always provide the ideal geometry for highlights, areas of very strong reflectance, regardless of the orientation of the surface or position of the receiver. Despite highlights and glossy appearance being common in chemically defended insects, their potential signalling function is unknown. We tested the role of highlights in warning colouration of a chemically defended, alpine leaf beetle, Oreina cacaliae. We reduced the beetles’ glossiness, hence their highlights, by applying a clear matt finish varnish on thei…
Do allopatric maleCalopteryx virgodamselflies learn species recognition?
2012
There is a growing amount of empirical evidence that premating reproductive isolation of two closely related species can be reinforced by natural selection arising from avoidance of maladaptive hybridization. However, as an alternative for this popular reinforcement theory, it has been suggested that learning to prefer conspecifics or to discriminate heterospecifics could cause a similar pattern of reinforced premating isolation, but this possibility is much less studied. Here, we report results of a field experiment in which we examined (i) whether allopatric Calopteryx virgo damselfly males that have not encountered heterospecific females of the congener C. splendens initially show discri…
Potential use of machine learning methods in assessment of Fusarium culmorum and Fusariumproliferatum growth and mycotoxin production in treatments w…
2021
Abstract The use of Fusarium-controlling fungicides is necessary to limit crop loss. Little is known about the effect of commercial antifungal formulations at sub-lethal doses, and their interaction with abiotic factors, on Fusarium culmorum and F. proliferatum development and on zearalenone and fumonisin biosynthesis, respectively. In the present study different treatments based on sulfur, trifloxystrobin and demethylation inhibitor fungicides (cyproconazole, tebuconazole and prothioconazole) under different environmental conditions, in Maize Extract Medium (MEM), are assayed in vitro. Then, several machine learning methods (neural networks, random forest and extreme gradient boosted trees…
Octopamine and dopamine mediate waggle dance following and information use in honeybees.
2020
Honeybees can be directed to profitable food sources by following waggle dances performed by other bees. Followers can often choose between using this social information or relying on memories about food sources they have visited in the past, so-called private information. While the circumstances that favour the use of either social or private information have received considerable attention, still little is known about the neurophysiological basis of information use. We hypothesized that octopamine and dopamine, two biogenic amines with important functions in reward signalling and learning, affect dance use in honeybees. We orally administered octopamine and dopamine when bees collected fo…
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation
2019
Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and image analysis for a wide range of applications in marine ecology. However, classifying fish from images captured by underwater cameras is in general very challenging due to noise and illumination variations in water. Previous classification methods in the literature relies on filtering the images to separate the fish from the background or sharpening the images by removing background noise. This pre-filtering process may negatively impact the classificat…
Nest defence against avian brood parasites is promoted by egg-removal events in a cowbird–host system
2011
Recent studies of birds have found that the antiparasite behaviour of host species is modified by social learning. We tested whether individual or social learning modifies the nest defence of yellow warblers, Setophaga petechia, against the parasitic brown-headed cowbird, Molothrus ater. Using field experiments, we exposed warblers to simulated events of nest parasitism and predation, or allowed them to observe conspecifics mobbing a cowbird. Intensity of nest defence by yellow warblers was greater after simulated threats at their nest than after they had observed mobbing of cowbirds by conspecifics. Warblers defended their nests more aggressively when they perceived a cowbird as an egg pre…
Anti-brood Parasite Defences: The Role of Individual and Social Learning
2017
In this chapter, we consider the ways in which learning is involved in the anti-brood parasitism defences that hosts deploy across the nesting cycle. Brood parasitism varies in space and through time, and hosts have accordingly evolved plastic defences that can be tuned to local conditions. Hosts can achieve their defence plasticity by individual and social learning, as well as by experience-independent mechanisms. While these mechanisms can profoundly affect the coevolutionary dynamics between hosts and their brood parasites, our understanding of how they feature across the host nesting cycle is far from complete. Hosts can actively defend themselves against brood parasitism via a variety …
Calibrating Expert Assessments Using Hierarchical Gaussian Process Models
2020
Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…
Benchmark database for fine-grained image classification of benthic macroinvertebrates
2018
Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…
On the Role of Perception: Understanding Stakeholders’ Collaboration in Natural Resources Management through the Evolutionary Theory of Innovation
2021
Natural resources management deals with highly complex socioecological systems. This complexity raises a conundrum, since wide-ranging knowledge from different sources and types is needed, but at the same time none of these types of knowledge is able by itself to provide the basis for a viable productive system, and mismatches between the two of them are common. Therefore, a growing body of literature has examined the integration of different types of knowledge in fisheries management. In this paper, we aim to contribute to this ongoing debate by integrating the evolutionary theory of innovation—and specifically the concept of proximity—and the theory of perception. We set up a theoretical …