A new methodology for computing birds’ 3D home ranges

Ferrarini, Alessandro; Giglio, Giuseppe; Pellegrino, Stefania Caterina; Frassanito, Anna Grazia; Gustin, Marco

doi:10.1186/s40657-018-0109-6

Cited by 11 publications

(8 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, we have applied GOI to 2D home ranges, however our overlap index can be readily applied to 3D home ranges as well (Tracey et al 2014;Ferrarini et al 2018b). In the case of volumetric home ranges, the 2D home range size should be simply replaced by 3D estimation, but GOI (and also GSI) would maintain the same properties described above.…”

Section: Discussionmentioning

confidence: 99%

“…It is present among Annex I species of EU Wild Birds Directive (2009/147/EEC), and its important breeding habitats have been designated as Special Protection Areas of the Natura 2000 Network. In Southern Italy, the Lesser Kestrel has been widely studied in the nearby colonies of Gravina in Puglia and Altamura (Gustin et al 2014a(Gustin et al , b, 2017aGustin et al 2014bGustin et al , 2017bGustin et al , 2018Ferrarini et al 2018a, b;Ferrarini et al 2018bFerrarini et al , 2019. The study area (Fig.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A new general index of home range overlap and segregation: the Lesser Kestrel in Southern Italy as a case study

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background There is increasing interest in evaluating home-range overlap (or, otherwise, segregation) between bird species, and between or within bird populations, to inform spatial planning. So far, studies of home-range overlap typically make use of comparisons between pairs of individuals, populations or species, and return a matrix of pairwise overlaps (e.g., percent overlaps). However, when the number of individuals, populations or species to be compared is elevated, an overlarge overlap matrix is difficult to interpret from an ecological viewpoint. Methods We propose here a new, conceptually simple and computationally efficient index (general overlap index; GOI) for the ready computation within GIS of home range overlap of an arbitrarily large number (i.e., n ≥ 2) of individuals, populations or species. Whatever the number of home ranges to be compared, GOI always returns a single score between 0 and 100. As a case study, we applied our index to 24,074 GPS points of 10 Lesser Kestrels (Falco naumanni) in order to estimate within-colony and between-colony overlaps in two neighboring colonies in Southern Italy. Results Within-colony overlap was elevated for both colonies (96.41% at Cassano delle Murge, n = 5 individuals; 81.38% at Santeramo in Colle, n = 5 individuals), while between-colony overlap was low (19.12%; n = 2 colonies) and, after a randomization procedure, more spatially-segregated than expected by chance. Conclusions Modern biotelemetry offers huge amounts of data describing the space use of animal species. The use of intuitive and straightforward indices, like GOI, can be useful to promptly extract ecological information from such an amount of data (e.g. detecting change in space use over successive years, evaluating the reliability of various home-range estimators).

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new general index of home range overlap and segregation: the Lesser Kestrel in Southern Italy as a case study

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…21 This can to some extent be alleviated through geometric methods 22 or by an alternative hexagonal representation of the 3D space. 23 Other 3D aspects of movement are captured by accelerometers (3D motion) and magnetometers (3D orientation) and this information can be used to augment other movement data. Data from these sensors need to be processed and analysed in different ways.…”

Section: Visual Analytics For Movementmentioning

confidence: 99%

Introduction to the special section on Visual Movement Analytics

Demšar

Slingsby

Weibel

2018

Information Visualization

View full text Add to dashboard Cite

“…Thus, there is good reason to believe that spatial dimensionality importantly affects animal movement. Efforts have been made previously to account for spatial dimensionality in the estimation of animal home ranges in the aerial and aquatic spatial domains where 2D+ movement is, perhaps, more obvious (Vivancos et al 2017, Ferrarini et al 2018. However, the extent to which comparable developments have occurred among terrestrial home range estimation is not as clear.…”

Section: Introductionmentioning

confidence: 99%

Landscape complexity persists as a critical source of bias in terrestrial animal home range estimation

Heit

Ortiz‐Calo

Montgomery

2021

Ecology

View full text Add to dashboard Cite

Home ranges provide a conceptual and quantitative representation of animal-habitat associations over time. Methods to estimate home ranges have swiftly progressed by dynamically accounting for various sources of bias. Across that period of growth, one potentially influential source of bias has yet to be robustly scrutinized. Animals inhabiting the terrestrial spatial domain make movement decisions in environments with variable landscape complexity.Despite that reality, home range estimation methods tend to be informed by two-dimensional (2D) data (i.e., X and Y coordinates) which analytically presume that these landscapes are flat. This analytical tendency potentially misrepresents the configuration and size of animal home range estimates. To examine the prevalence of this bias, we reviewed literature of terrestrial animal home range estimation published between 2000 and 2019. We recorded the proportion of studies that; i) recognized and ii) incorporated landscape complexity. Over 22.0% (n = 271) of the 1,203 studies recognized the importance of landscape complexity for animal movement. Interestingly, just 0.7% (n = 8) incorporated landscape complexity into the home range estimation. We infer then that landscape complexity represents an important source of bias resulting in the underestimation of terrestrial animal home range size. Given the influence of landscape complexity on terrestrial animal decision-making, energetics, and fitness our analysis highlights an important gap in current home range methodologies. We discuss the implications of our analysis for biased understandings of terrestrial animal spatial ecology with subsequent impacts on management and conservation practices built upon these estimates.

show abstract

A new methodology for computing birds’ 3D home ranges

Cited by 11 publications

References 12 publications

A new general index of home range overlap and segregation: the Lesser Kestrel in Southern Italy as a case study

A new general index of home range overlap and segregation: the Lesser Kestrel in Southern Italy as a case study

Introduction to the special section on Visual Movement Analytics

Landscape complexity persists as a critical source of bias in terrestrial animal home range estimation

Contact Info

Product

Resources

About