Habitat Suitability Models, for ecological study of the alpine marmot in the central Italian Alps

Galluzzi, Marta; Armanini, Marco; Ferrari, Giulia; Zibordi, Filippo; Nocentini, Susanna; Mustoni, Andrea

doi:10.1016/j.ecoinf.2016.11.010

Cited by 6 publications

(3 citation statements)

References 33 publications

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“…Worldwide, there are 14 marmot species which are large burrowing and hibernating squirrels [26,33]. They have adopted various survival tactics to cope with habitat stimuli, such as changing time rhythm [18,19], or using habitats farther away from human activity [34][35][36], or constructed extra burrows for shelter (e.g., Vancouver Island marmot M. vancouverensis [37]as well as selected big stones to facilitate better scanning (e.g., Alpine marmot M. marmot [34,38] and used predated rocky burrows to reduce threats (e.g., golden marmot M. caudata aurea [15]. Ecologically, marmots are important prey for Golden Eagle (Aquila chrysaetos), Tibetan wolf (Canis lupus chancho) and snow leopard (Panthera uncia) [39,40].…”

Section: Journal Of Ethology and Animal Sciencementioning

confidence: 99%

The Long and Winding Road in the Cross-Process among Authors and Editors must not Fall into Pandora's Box: The Role of Reviewers

Zaman¹

2022

JEASc

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Animals may change the temporal dimension of their niche by shifting their activity patterns in relation to anthropogenic disturbances. Yet, few studies have documented these response phenomena in pasture land. We examined the extent to which disturbances related with habitat features altered the timing of foraging and activity patterns of golden marmot (Marmota caudata aurea). Using a scan-sampling observational method, we collected data from 34 pup-rearing marmot burrow sites in the summer pasture area of Shigar Valley, northwest Pakistan. We defined frequency of occurrences index (FOI) of anthropogenic disturbance intensity for each site based on the presence of livestock, herders, distance from livestock corrals or shepherd huts, and density of major tracks, and determined whether marmot time spent aboveground, as well as foraging distance from pup-burrows, was or not between high and low disturbance sites. We found that disturbance intensity influenced the total daily activity time and foraging distance from pup burrows. Our results indicated that marmots adjusted their diurnal patterns of activity and the distances moved from their pup burrows in relation to the timing of anthropogenic activities implying changes to the temporal and spatial dimension of their niche. In areas with high levels of disturbance, marmots were less active during morning periods and more active during midday and compensated by increasing activity when herding activity was less. Foraging activity was less during midday and showed a peak during late evening. Finally, results suggest that grazing intensity of human disturbances may have significant consequences in terms of marmot summer pup-raising periods for energy intake

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Section: Journal Of Ethology and Animal Sciencementioning

confidence: 99%

The Long and Winding Road in the Cross-Process among Authors and Editors must not Fall into Pandora's Box: The Role of Reviewers

Zaman¹

2022

JEASc

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“…La Ecología es la ciencia que estudia las interacciones entre los seres vivos (plantas, animales y humanos) entre sí y con el medio ambiente en el que viven [1]. En las posibilidades de vida de un determinado animal o planta influyen diversos factores.…”

Section: Introductionunclassified

“…El interés de identificar estas especies, parte del hecho, que son animales morfológicamente parecidos, lo que convierte el problema de identificarlos en un problema desafiante, en el tema de identificación y clasificación de imágenes, aparte del impacto en la protección de la importante comunidad ecológica [1].…”

Section: Introductionunclassified

Identification of Rodent Species Using Deep Learning

Seijas

Montilla²,

Frassato³

2019

CyS

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En este artículo se describe un sistema identificador de especies de roedores usando herramientas computacionales del paradigma de aprendizaje profundo. Las especies identificadas son 4 tipos diferentes de roedores y la identificación se logra usando técnicas de inteligencia artificial aplicadas a imágenes de estos roedores en su hábitat natural. Estas imágenes fueron captadas, mediante sistemas de cámaras activadas en modo automático, ocultas en el hábitat natural de las especies en estudio, en condiciones, tanto, de luz del día como también nocturnas y etiquetadas por expertos. El conjunto de imágenes acopiada constituye el conjunto de datos para entrenamiento de tipo supervisado, de 1411 imágenes de 4 clases. El identificador desarrollado, es un clasificador multiclase, basado en el paradigma de aprendizaje profundo del amplio tema del aprendizaje automático, lo que permite construir un sistema de altísimo desempeño. El clasificador consta de tres etapas conectadas en cascada, siendo la primera etapa, una etapa de pre-procesamiento, luego, está una red neuronal convolucional (CNN, de sus siglas en inglés) para extracción de rasgos, implementada con una arquitectura pre-entrenada usando el método de aprendizaje por transferencia; específicamente, la CNN usada es la conocida VGG-16; a esta segunda etapa, se le conecta como etapa siguiente y final, una máquina de vectores de soporte (SVM, de sus siglas en inglés) que actúa como la etapa clasificadora. A fines de comparación, los resultados se contrastan contra modelos de identificación automáticos anteriormente publicados, los resultados logrados con nuestro identificador son significativamente superiores a los alcanzados en investigaciones previas en el tema. Palabras claves.Identificación de especies, aprendizaje profundo, red neuronal convolucional preentrenada.Abstract. In this article, we describe a rodent species identification system using computational tools of the deep learning paradigm. The identified species are 4 different types of rodents and the identification is achieved using artificial intelligence techniques applied to images of these rodents in their natural habitat. These images were captured, using camera systems activated in automatic mode, hidden in the natural habitat of the species under study, under both daylight and nighttime conditions and labeled by experts. The collected image set constitutes the data set for supervised training of 1411 images of 4 classes. The identifier developed is a multiclass classifier, based on the deep learning paradigm of the broad topic of machine learning, which allows to build a high performance system. The classifier consists of three stages connected in cascade, being the first stage, a pre-processing stage, then, there is a convolutional neural network (CNN) for feature extraction, implemented with a pre-trained architecture using the method of learning by transfer; specifically, the CNN used is the well-known VGG-16; to this second stage, a support vector machine (SVM) is connected as the next and fin...

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Symbolic species as a cultural ecosystem service in the European Alps: insights and open issues

Schirpke

Meisch

2018

Landscape Ecol

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Purpose Symbolic plants and animals are recognised as a cultural ecosystem service (CES), which is still underrepresented in ecosystem services assessments. Thus, this study aims at identifying and mapping important symbolic species in the European Alps, which are of cultural significance to large parts of the Alpine population. Methods Symbolic species were identified by ten expert groups, and their use was assessed in a qualitative way. The spatial distribution of all species across the Alpine Space area was mapped at the municipality level. Through hotspots analysis, we identified spatial patterns in the distribution of species. Spearman correlation was used to evaluate the relationship between symbolic species and selected environmental and social variables. Results Ten species were identified (edelweiss, gentian, alpenrose, larch, pine, Alpine ibex, chamois, marmot, brown bear, and golden eagle) that are widely used for symbolic representations, i.e., depiction on flags, emblems, logos, and naming of hotels and brands. Hotspots of symbolic species were found in several locations in the European Alps and could be related to high elevation, steep slopes, open land cover, and naturalness. Conclusions This study proposes a methodology to map and assess symbolic species as a CES. As the spatial distribution of symbolic species depends on environmental characteristics and human activities, our results provide important insights for landscape planning and management. However, it remains unclear whether associated cultural values depend on the presence of the species and further research is needed to understand the relationships between the distribution of symbolic species and social benefits.

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Habitat Suitability Models, for ecological study of the alpine marmot in the central Italian Alps

Cited by 6 publications

References 33 publications

The Long and Winding Road in the Cross-Process among Authors and Editors must not Fall into Pandora's Box: The Role of Reviewers

The Long and Winding Road in the Cross-Process among Authors and Editors must not Fall into Pandora's Box: The Role of Reviewers

Identification of Rodent Species Using Deep Learning

Symbolic species as a cultural ecosystem service in the European Alps: insights and open issues

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