scholarly journals Individual variation in the dear enemy phenomenon via territorial vocalizations in red squirrels

2018 ◽  
Author(s):  
Jack Graham Robertson ◽  
Stan Boutin ◽  
Murray M Humphries ◽  
Ben Dantzer ◽  
Jeffrey E Lane ◽  
...  
Keyword(s):  
Individual Variation ◽  
Binary Classification ◽  
Variable Importance ◽  
Tamiasciurus Hudsonicus ◽  
Red Squirrels ◽  
Dear Enemy ◽  
Dear Enemy Phenomenon ◽  
Replacement Experiment

Territoriality arises when the benefits of resources exceed the costs of defending them. The dear enemy phenomenon, where familiar territorial neighbours refrain from intruding on one another and mutually reduce their defensive efforts, allows for reduction of these costs but requires discrimination between conspecifics. We hypothesized that territorial vocalizations in red squirrels (Tamiasciurus hudsonicus) are used for this discrimination. We performed a speaker replacement experiment where red squirrels (n = 41) were temporarily removed from their territories and replaced with a speaker broadcasting their own call, an unfamiliar call, or silence. Contrary to our prediction, there were no differences in overall intrusion risk among our three playbacks, but the identity of intruders did vary. Existing variation in familiarity within territorial neighbourhoods should be considered, rather than the binary classification of familiar or stranger, when studying dear enemy effects. We also discuss the variable importance of silence in acoustic territorial populations.

scholarly journals Individual variation in the dear enemy phenomenon via territorial vocalizations in red squirrels

Behaviour ◽  
2018 ◽  
Vol 155 (13-15) ◽  
pp. 1073-1096
Author(s):  
Jack G. Robertson ◽  
Stan Boutin ◽  
Murray M. Humphries ◽  
Ben Dantzer ◽  
Jeffrey E. Lane ◽  
...  
Keyword(s):  
Individual Variation ◽  
Binary Classification ◽  
Variable Importance ◽  
Tamiasciurus Hudsonicus ◽  
Red Squirrels ◽  
Dear Enemy ◽  
Dear Enemy Phenomenon ◽  
Replacement Experiment

Abstract Territoriality arises when the benefits of resources exceed the costs of defending them. The dear enemy phenomenon, where familiar territorial neighbours refrain from intruding on one another and mutually reduce their defensive efforts, allows for reduction of these costs but requires discrimination between conspecifics. We hypothesized that territorial vocalizations in red squirrels (Tamiasciurus hudsonicus) are used for this discrimination. We performed a speaker replacement experiment where red squirrels () were temporarily removed from their territories and replaced with a speaker broadcasting their own call, an unfamiliar call, or silence. Contrary to our prediction, there were no differences in overall intrusion risk among our three playbacks, but the identity of intruders did vary. Existing variation in familiarity within territorial neighbourhoods should be considered, rather than the binary classification of familiar or stranger, when studying dear enemy effects. We also discuss the variable importance of silence in acoustic territorial populations.

The ability of red squirrels (Tamiasciurus hudsonicus) to discriminate conspecific olfactory signatures

2001 ◽  
Vol 79 (7) ◽  
pp. 1296-1300 ◽  
Author(s):  
Marion Vaché ◽  
Jean Ferron ◽  
Patrick Gouat
Keyword(s):  
Boreal Forest ◽  
Vocal Communication ◽  
Tamiasciurus Hudsonicus ◽  
Olfactory Communication ◽  
Red Squirrels ◽  
Dear Enemy ◽  
Dear Enemy Phenomenon

Using a habituation-dishabituation procedure, we investigated the ability of male red squirrels (Tamiasciurus hudsonicus) to discriminate olfactory signatures of different male conspecifics. Our results indicate that they effectively pay attention to odours from unfamiliar male conspecifics and that they invest more time sniffing litter impregnated with these unfamiliar social odours than control litters. They can also habituate themselves to a given social odour and can discriminate olfactory signatures of different male conspecifics. The role of olfactory communication in this territorial species from the boreal forest is discussed with regard to the "dear enemy" phenomenon and to the fact that these squirrels are known to use vocal communication intensively to advertise their territories.

scholarly journals Individual variation in phenotypic plasticity of the stress axis

2019 ◽  
Author(s):  
Sarah Guindre-Parker ◽  
Andrew G. Mcadam ◽  
Freya Van Kesteren ◽  
Rupert Palme ◽  
Rudy Boonstra ◽  
...  
Keyword(s):  
Phenotypic Plasticity ◽  
Individual Variation ◽  
Local Density ◽  
Reaction Norm ◽  
Tamiasciurus Hudsonicus ◽  
Stress Axis ◽  
Red Squirrels ◽  
Conspecific Density ◽  
North American Red Squirrels ◽  
Future Work

ABSTRACTPhenotypic plasticity—one individual’s capacity for phenotypic variation under different environments—is critical for organisms facing fluctuating conditions within their lifetime. North American red squirrels (Tamiasciurus hudsonicus) experience drastic among-year fluctuations in conspecific density. This shapes juvenile competition over vacant territories and overwinter survival. To help young cope with competition at high densities, mothers can increase offspring growth rates via a glucocorticoid-mediated maternal effect. However, this effect is only adaptive under high densities, and faster growth often comes at a cost to longevity. While experiments have demonstrated that red squirrels can adjust hormones in response to fluctuating density, the degree to which mothers differ in their ability to regulate glucocorticoids across changing densities remains unknown—little is known about within-individual plasticity in endocrine traits relative to among-individual variation. Findings from our reaction norm approach revealed significant individual variation not only in a female red squirrel’s mean endocrine phenotype, but also in endocrine plasticity in response to changes in local density. Future work on the proximate and ultimate drivers of variation in the plasticity of endocrine traits and maternal effects is needed, particularly in free-living animals experiencing fluctuating environments.

scholarly journals Individual variation in phenotypic plasticity of the stress axis

2019 ◽  
Vol 15 (7) ◽  
pp. 20190260 ◽  
Author(s):  
Sarah Guindre-Parker ◽  
Andrew G. Mcadam ◽  
Freya van Kesteren ◽  
Rupert Palme ◽  
Rudy Boonstra ◽  
...  
Keyword(s):  
Phenotypic Plasticity ◽  
Individual Variation ◽  
Local Density ◽  
Reaction Norm ◽  
Tamiasciurus Hudsonicus ◽  
Stress Axis ◽  
Red Squirrels ◽  
Conspecific Density ◽  
North American Red Squirrels ◽  
Future Work

Phenotypic plasticity—one individual's capacity for phenotypic variation under different environments—is critical for organisms facing fluctuating conditions within their lifetime. North American red squirrels ( Tamiasciurus hudsonicus ) experience drastic among-year fluctuations in conspecific density. This shapes juvenile competition over vacant territories and overwinter survival. To help young cope with competition at high densities, mothers can increase offspring growth rates via a glucocorticoid-mediated maternal effect. However, this effect is only adaptive under high densities, and faster growth often comes at a cost to longevity. While red squirrels can adjust hormones in response to fluctuating density, the degree to which mothers differ in glucocorticoid plasticity across changing densities remains unknown. Findings from our reaction norm approach revealed significant individual variation not only in a female red squirrel's mean endocrine phenotype but also in endocrine plasticity in response to changes in local density. Future work on proximate and ultimate drivers of variation in endocrine plasticity and maternal effects is needed, particularly in free-living animals experiencing fluctuating environments.

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

A Study on Multi Class Classification from Breast Cancer Images using Ensemble Network and Transfer Learning

2020 ◽  
Vol 14 ◽  
Author(s):  
Lahari Tipirneni ◽  
Rizwan Patan
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Convolutional Neural Network ◽  
Binary Classification ◽  
Disease Diagnosis ◽  
Feature Descriptors ◽  
Histopathological Images ◽  
Viable Approach ◽  
Multi Class Classification

Abstract:: Millions of deaths all over the world are caused by breast cancer every year. It has become the most common type of cancer in women. Early detection will help in better prognosis and increases the chance of survival. Automating the classification using Computer-Aided Diagnosis (CAD) systems can make the diagnosis less prone to errors. Multi class classification and Binary classification of breast cancer is a challenging problem. Convolutional neural network architectures extract specific feature descriptors from images, which cannot represent different types of breast cancer. This leads to false positives in classification, which is undesirable in disease diagnosis. The current paper presents an ensemble Convolutional neural network for multi class classification and Binary classification of breast cancer. The feature descriptors from each network are combined to produce the final classification. In this paper, histopathological images are taken from publicly available BreakHis dataset and classified between 8 classes. The proposed ensemble model can perform better when compared to the methods proposed in the literature. The results showed that the proposed model could be a viable approach for breast cancer classification.

scholarly journals Improving Land Cover Classification Using Genetic Programming for Feature Construction

2021 ◽  
Vol 13 (9) ◽  
pp. 1623
Author(s):  
João E. Batista ◽  
Ana I. R. Cabral ◽  
Maria J. P. Vasconcelos ◽  
Leonardo Vanneschi ◽  
Sara Silva
Keyword(s):  
Land Cover ◽  
Genetic Programming ◽  
Satellite Images ◽  
State Of The Art ◽  
Binary Classification ◽  
Feature Construction ◽  
Classification Problems ◽  
Construction Methods ◽  
Box Models

Genetic programming (GP) is a powerful machine learning (ML) algorithm that can produce readable white-box models. Although successfully used for solving an array of problems in different scientific areas, GP is still not well known in the field of remote sensing. The M3GP algorithm, a variant of the standard GP algorithm, performs feature construction by evolving hyperfeatures from the original ones. In this work, we use the M3GP algorithm on several sets of satellite images over different countries to create hyperfeatures from satellite bands to improve the classification of land cover types. We add the evolved hyperfeatures to the reference datasets and observe a significant improvement of the performance of three state-of-the-art ML algorithms (decision trees, random forests, and XGBoost) on multiclass classifications and no significant effect on the binary classifications. We show that adding the M3GP hyperfeatures to the reference datasets brings better results than adding the well-known spectral indices NDVI, NDWI, and NBR. We also compare the performance of the M3GP hyperfeatures in the binary classification problems with those created by other feature construction methods such as FFX and EFS.

scholarly journals Potential of Small Culverts as Wildlife Passages on Forest Roads

2021 ◽  
Vol 13 (13) ◽  
pp. 7224
Author(s):  
Hsiang-Ling Chen ◽  
Erin E. Posthumus ◽  
John L. Koprowski
Keyword(s):  
Animal Movement ◽  
Small Dimension ◽  
Lynx Rufus ◽  
Tamiasciurus Hudsonicus ◽  
Red Squirrels ◽  
Forest Roads ◽  
Alternative Pathways ◽  
Slow Moving ◽  
Trail Cameras ◽  
Spermophilus Variegatus

Roads and traffic can cause animal mortality. Specifically, roads serve as barriers by impeding animal movement, resulting in demographic and genetic consequences. Drainage structures, such as culverts, can provide linkages between habitat patches. However, the potential of small culverts with diameters of <60 cm (e.g., wildlife passages that facilitate movement on forest roads) are relatively unknown. In this study, we used trail cameras to monitor the use of 14 small culverts, by mammals, along forest roads on Mt. Graham, home of the critically endangered Mt. Graham red squirrels (Tamiasciurus hudsonicus grahamensis), in southeastern Arizona, USA. From 2011 to 2013, we only recorded 20 completed road crossings through culverts. More than half of culvert uses were by striped skunks (Mephitis mephitis), followed by the rock squirrel (Spermophilus variegatus) and the bobcat (Lynx rufus). The Mt. Graham red squirrel was the only species that was common along the roads, but never crossed the roads. Culverts with higher usages were characterized by shorter culvert lengths and absence of accumulated soil inside the culverts. Our study shows that small-dimension drainage systems may provide alternative pathways for wildlife crossing roads, especially for slow moving and ground dwelling species. However, the potential of small culverts assisting wildlife crossings can only be maximized when culverts are accessible year-round.

scholarly journals Monotonic Functions Method and Its Application to Staging of Patients with Prostate Cancer According to Pretreatment Data

2021 ◽  
Vol 11 (9) ◽  
pp. 3836
Author(s):  
Valeri Gitis ◽  
Alexander Derendyaev ◽  
Konstantin Petrov ◽  
Eugene Yurkov ◽  
Sergey Pirogov ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Learning Algorithm ◽  
Binary Classification ◽  
Preoperative Staging ◽  
Threshold Value ◽  
Logical Function ◽  
Adequate Treatment ◽  
Monotonic Functions ◽  
Selection Of

Prostate cancer is the second most frequent malignancy (after lung cancer). Preoperative staging of PCa is the basis for the selection of adequate treatment tactics. In particular, an urgent problem is the classification of indolent and aggressive forms of PCa in patients with the initial stages of the tumor process. To solve this problem, we propose to use a new binary classification machine-learning method. The proposed method of monotonic functions uses a model in which the disease’s form is determined by the severity of the patient’s condition. It is assumed that the patient’s condition is the easier, the less the deviation of the indicators from the normal values inherent in healthy people. This assumption means that the severity (form) of the disease can be represented by monotonic functions from the values of the deviation of the patient’s indicators beyond the normal range. The method is used to solve the problem of classifying patients with indolent and aggressive forms of prostate cancer according to pretreatment data. The learning algorithm is nonparametric. At the same time, it allows an explanation of the classification results in the form of a logical function. To do this, you should indicate to the algorithm either the threshold value of the probability of successful classification of patients with an indolent form of PCa, or the threshold value of the probability of misclassification of patients with an aggressive form of PCa disease. The examples of logical rules given in the article show that they are quite simple and can be easily interpreted in terms of preoperative indicators of the form of the disease.

Jack pine cone quality and cache sizes of red squirrels in southern New Brunswick, Canada

1997 ◽  
Vol 75 (2) ◽  
pp. 332-335 ◽  
Author(s):  
Michael A. Setterington ◽  
Daniel M. Keppie
Keyword(s):  
New Brunswick ◽  
Pinus Banksiana ◽  
Seed Mass ◽  
Dry Mass ◽  
Jack Pine ◽  
Tamiasciurus Hudsonicus ◽  
Red Squirrels ◽  
Length Width ◽  
Total Seed ◽  
Number Of Seeds

Relationships between external cone characteristics (length, width, wet and dry mass), cone quality (total seed mass as a proportion of cone mass, total number of seeds per cone, total seed mass per cone), and number of cones in caches were evaluated for caches of jack pine (Pinus banksiana) cones belonging to red squirrels (Tamiasciurus hudsonicus) in two plantations in southern New Brunswick. Cone length and mass were good predictors of the total number of seeds per cone and total seed mass per cone. Length accounted for a small proportion of the variance of total seed mass as a proportion of cone mass. There was no relationship between the number of seeds or total seed mass per cone and the number of cones per cache.

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