Vertebrate Conservation and Biodiversity

Hawksworth, David L.; Bull, Alan T.

doi:10.1007/978-1-4020-6320-6

Cited by 4 publications

(2 citation statements)

References 399 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Maned wolves are a savannah adapted vulnerable species of omnivores found south of the Amazon Forest (Figure 1A). The main threat to the species comes from the continuous large-scale habitat losses (Noss and Lima, 2007), which are especially significant in Brazil because of the extensive conversion of Brazilian savannah into farmland (Fonseca et al, 1994). The Serra da Canastra National Park (CNP) (Figure 1B) has been key to the preservation of maned wolves and it is the home of the wolves whose tracking data are used in this study.…”

Section: Movement Data and Study Areamentioning

confidence: 99%

Using eigen decomposition and sequence-based representation to extract movement patterns from contextualized tracking data

Brum-Bastos

Long

Demšar

2021

AGILE GIScience Ser.

View full text Add to dashboard Cite

Abstract. State sequences are a new paradigm to encode and represent contextualised movement data. A state sequence is a temporal succession of characters representing categorical states of the moving entity or its surrounding environment. Eigen decomposition, a principal components analysis method, is an option to reduce and find patterns in such multi-dimensional categorical data through dimensionality reduction. Recurrent patterns can be found by identifying the most relevant eigenbehaviours, which are a set of vectors that characterize the variation in the behaviour of an entity during a time period. Dimensionality reduction techniques have so far not been widely used in movement analytics and in this paper we demonstrate how they could help analyse responses of a moving entity to the dynamic environmental conditions. Specifically, we use sequence-based representation and eigen decomposition to investigate movement patterns of maned wolves (Chrysocyon brachyurus) in relation to vegetation vigour in their habitat. We use a set of GPS-trajectories from a group of maned wolves to which we link multi-source NDVI data as a proxy for the state of vegetation. We find that eigenbehaviours can identify patterns in the wolves’ responses to dynamic environmental conditions that align with the current literature on the species. Our research highlights the potential for dimensionality reduction and sequence-based methods to identify patterns in large tracking databases linked to contextual data.

show abstract

Section: Movement Data and Study Areamentioning

confidence: 99%

Using eigen decomposition and sequence-based representation to extract movement patterns from contextualized tracking data

Brum-Bastos

Long

Demšar

2021

AGILE GIScience Ser.

View full text Add to dashboard Cite

show abstract

“…Considered "vulnerable" until 1996 by IUCN (International Union for Conservation of Nature), the species is currently classified as "near threatened" (de Paula and DeMatteo, 2015) and "vulnerable" by the Brazilian environmental authorities (ICMBio, 2016). The main threat to the species comes from the continuous large scale habitat loss (Noss and Lima, 2007) which is especially significant in Brazil because of the extensive conversion of the Cerrado (Brazilian savannah) into farmland (Fonseca et al, 1994). Only 20% of Cerrado is still covered by native vegetation (Myers et al, 2000) and less than 2.5% is protected by law.…”

Section: Study Area and Speciesmentioning

confidence: 99%

Multi-source data fusion of optical satellite imagery to characterize habitat selection from wildlife tracking data

Brum-Bastos

Long

Church

et al. 2020

Ecological Informatics

View full text Add to dashboard Cite

Wildlife tracking data allow monitoring of how organisms respond to spatio-temporal changes in resource availability. Remote sensing data can be used to quantify and qualify these variations to understand how movement is related to these changes. The use of remote sensing data with concurrent high levels of spatial and temporal detail may hold potential to improve our understanding of habitat selection. However, no current orbital sensor produces data with simultaneous high temporal and high spatial resolution, therefore alternative methods are required to generate remote sensing data that matches the high spatial-temporal resolution of

show abstract

How Hunting and Wildlife Conservation Can Coexist: Review and Case Studies

Perco¹

2020

Problematic Wildlife II

View full text Add to dashboard Cite

Vertebrate Conservation and Biodiversity

Cited by 4 publications

References 399 publications

Using eigen decomposition and sequence-based representation to extract movement patterns from contextualized tracking data

Using eigen decomposition and sequence-based representation to extract movement patterns from contextualized tracking data

Multi-source data fusion of optical satellite imagery to characterize habitat selection from wildlife tracking data

How Hunting and Wildlife Conservation Can Coexist: Review and Case Studies

Contact Info

Product

Resources

About