Revisiting reptile home ranges: moving beyond traditional estimators with dynamic Brownian Bridge Movement Models

A fresh look at an old concept: Home-range estimation in a tidy world

10.1101/2020.08.19.256859 ◽

2020 ◽

Cited By ~ 1

Author(s):

Johannes Signer ◽

John Fieberg

Keyword(s):

Home Range ◽

General Framework ◽

Point Of View ◽

Home Ranges ◽

List Type ◽

Telemetry Data ◽

Range Estimation ◽

Computational Point ◽

Qualitative And Quantitative ◽

New Methods

AbstractA rich set of statistical techniques have been developed over the last several decades to estimate the spatial extent of animal home ranges from telemetry data, and new methods to estimate home ranges continue to be developed.Here we investigate home-range estimation from a computational point of view and aim to provide a general framework for computing home ranges, independent of specific estimators.We show how such a workflow can help make home-range estimation easier and more intuitive, and we provide a series of examples illustrating how different estimators can be compared easily, so that one can perform a sensitivity analysis to determine the degree to which the choice of estimator influences qualitative and quantitative conclusions.By providing a standardized, tidy implementation of home-range estimators, we hope to equip analysts with the tools needed to explore how estimator choice influences answers to biologically meaningful questions.

Using dynamic Brownian Bridge Movement Models to identify home range size and movement patterns in king cobras

PLoS ONE ◽

10.1371/journal.pone.0203449 ◽

2018 ◽

Vol 13 (9) ◽

pp. e0203449 ◽

Cited By ~ 8

Author(s):

Inês Silva ◽

Matthew Crane ◽

Pongthep Suwanwaree ◽

Colin Strine ◽

Matt Goode

Keyword(s):

Home Range ◽

Brownian Bridge ◽

Movement Patterns ◽

Home Range Size ◽

Range Size ◽

Movement Models

Home-range estimation within complex restricted environments: importance of method selection in detecting seasonal change

Wildlife Research ◽

10.1071/wr08032 ◽

2009 ◽

Vol 36 (3) ◽

pp. 213 ◽

Cited By ~ 21

Author(s):

Carolyn M. Knight ◽

Robert E. Kenward ◽

Rodolphe E. Gozlan ◽

Kathryn H. Hodder ◽

Sean S. Walls ◽

...

Keyword(s):

Cluster Analysis ◽

Seasonal Variation ◽

Home Range ◽

Reserve Design ◽

Linear Estimator ◽

Home Ranges ◽

Telemetry Data ◽

Range Estimation ◽

River Bank ◽

Wide Range

Estimating the home ranges of animals from telemetry data can provide vital information on their spatial behaviour, which can be applied by managers to a wide range of situations including reserve design, habitat management and interactions between native and non-native species. Methods used to estimate home ranges of animals in spatially restricted environments (e.g. rivers) are liable to overestimate areas and underestimate travel distances by including unusable habitat (e.g. river bank). Currently, few studies that collect telemetry data from species in restricted environments maximise the information that can be gathered by using the most appropriate home-range estimation techniques. Simulated location datasets as well as radio-fix data from 23 northern pike (Esox lucius) were used to examine the efficiency of home-range and travel estimators, with and without correction for unusable habitat, for detecting seasonal changes in movements. Cluster analysis most clearly demonstrated changes in range area between seasons for empirical data, also showing changes in patchiness, and was least affected by unusable-environment error. Kernel analysis showed seasonal variation in range area more clearly than peripheral polygons or ellipses. Range span, a linear estimator of home range, had no significant seasonal variation. Results from all range area estimators were smallest in autumn, when cores were least fragmented and interlocation movements smallest. Cluster analysis showed that core ranges were largest and most fragmented in summer, when interlocation distances were most variable, whereas excursion-sensitive methods (e.g. kernels) recorded the largest outlines in spring, when interlocation distances were largest. Our results provide a rationale for a priori selection of home-range estimators in restricted environments. Contours containing 95% of the location density defined by kernel analyses better reflected excursive activity than ellipses or peripheral polygons, whereas cluster analyses better defined range cores in usable habitat and indicate range fragmentation.

Reptiles on the wrong track? Moving beyond traditional estimators with dynamic Brownian Bridge Movement Models

Movement Ecology ◽

10.1186/s40462-020-00229-3 ◽

2020 ◽

Vol 8 (1) ◽

Author(s):

Inês Silva ◽

Matt Crane ◽

Benjamin Michael Marshall ◽

Colin Thomas Strine

Keyword(s):

Home Range ◽

High Frequency ◽

Brownian Bridge ◽

Space Use ◽

Estimation Methods ◽

Tracking Data ◽

Movement Models ◽

Frequency Sampling ◽

Research Questions

Abstract Background Animal movement expressed through home ranges or space-use can offer insights into spatial and habitat requirements. However, different classes of estimation methods are currently instinctively applied to answer home range, space-use or movement-based research questions regardless of their widely varying outputs, directly impacting conclusions. Recent technological advances in animal tracking (GPS and satellite tags), have enabled new methods to quantify animal space-use and movement pathways, but so far have primarily targeted mammal and avian species. Methods Most reptile spatial ecology studies only make use of two older home range estimation methods: Minimum Convex Polygons (MCP) and Kernel Density Estimators (KDE), particularly with the Least Squares Cross Validation (LSCV) and reference (href) bandwidth selection algorithms. These methods are frequently applied to answer space-use and movement-based questions. Reptile movement patterns are unique (e.g., low movement frequency, long stop-over periods), prompting investigation into whether newer movement-based methods –such as dynamic Brownian Bridge Movement Models (dBBMMs)– apply to Very High Frequency (VHF) radio-telemetry tracking data. We simulated movement data for three archetypical reptile species: a highly mobile active hunter, an ambush predator with long-distance moves and long-term sheltering periods, and an ambush predator with short-distance moves and short-term sheltering periods. We compared traditionally used estimators, MCP and KDE, with dBBMMs, across eight feasible VHF field sampling regimes for reptiles, varying from one data point every four daylight hours, to once per month. Results Although originally designed for GPS tracking studies, dBBMMs outperformed MCPs and KDE href across all tracking regimes in accurately revealing movement pathways, with only KDE LSCV performing comparably at some higher frequency sampling regimes. However, the LSCV algorithm failed to converge with these high-frequency regimes due to high site fidelity, and was unstable across sampling regimes, making its use problematic for species exhibiting long-term sheltering behaviours. We found that dBBMMs minimized the effect of individual variation, maintained low error rates balanced between omission (false negative) and commission (false positive), and performed comparatively well even under low frequency sampling regimes (e.g., once a month). Conclusions We recommend dBBMMs as a valuable alternative to MCP and KDE methods for reptile VHF telemetry data, for research questions associated with space-use and movement behaviours within the study period: they work under contemporary tracking protocols and provide more stable estimates. We demonstrate for the first time that dBBMMs can be applied confidently to low-resolution tracking data, while improving comparisons across regimes, individuals, and species.

A fresh look at an old concept: home-range estimation in a tidy world

PeerJ ◽

10.7717/peerj.11031 ◽

2021 ◽

Vol 9 ◽

pp. e11031

Author(s):

Johannes Signer ◽

John R. Fieberg

Keyword(s):

Home Range ◽

General Framework ◽

Point Of View ◽

Statistical Techniques ◽

Home Ranges ◽

Telemetry Data ◽

Range Estimation ◽

Computational Point ◽

Qualitative And Quantitative ◽

New Methods

A rich set of statistical techniques has been developed over the last several decades to estimate the spatial extent of animal home ranges from telemetry data, and new methods to estimate home ranges continue to be developed. Here we investigate home-range estimation from a computational point of view and aim to provide a general framework for computing home ranges, independent of specific estimators. We show how such a workflow can help to make home-range estimation easier and more intuitive, and we provide a series of examples illustrating how different estimators can be compared easily. This allows one to perform a sensitivity analysis to determine the degree to which the choice of estimator influences qualitative and quantitative conclusions. By providing a standardized implementation of home-range estimators, we hope to equip researchers with the tools needed to explore how estimator choice influences answers to biologically meaningful questions.

Movement patterns of feral predators in an arid environment – implications for control through poison baiting

Wildlife Research ◽

10.1071/wr08098 ◽

2009 ◽

Vol 36 (5) ◽

pp. 422 ◽

Cited By ~ 64

Author(s):

K. E. Moseby ◽

J. Stott ◽

H. Crisp

Keyword(s):

Home Range ◽

Sand Dunes ◽

Activity Patterns ◽

Movement Patterns ◽

Home Range Size ◽

Range Size ◽

Home Ranges ◽

Feral Cats ◽

Poison Baiting ◽

Specific Variation

Control of introduced predators is critical to both protection and successful reintroduction of threatened prey species. Efficiency of control is improved if it takes into account habitat use, home range and the activity patterns of the predator. These characteristics were studied in feral cats (Felis catus) and red foxes (Vulpes vulpes) in arid South Australia, and results are used to suggest improvements in control methods. In addition, mortality and movement patterns of cats before and after a poison-baiting event were compared. Thirteen cats and four foxes were successfully fitted with GPS data-logger radio-collars and tracked 4-hourly for several months. High intra-specific variation in cat home-range size was recorded, with 95% minimum convex polygon (MCP) home ranges varying from 0.5 km2 to 132 km2. Cat home-range size was not significantly different from that of foxes, nor was there a significant difference related to sex or age. Cats preferred habitat types that support thicker vegetation cover, including creeklines and sand dunes, whereas foxes preferred sand dunes. Cats used temporary focal points (areas used intensively over short time periods and then vacated) for periods of up to 2 weeks and continually moved throughout their home range. Aerial baiting at a density of 10 baits per km2 was ineffective for cats because similar high mortality rates were recorded for cats in both baited and unbaited areas. Mortality was highest in young male cats. Long-range movements of up to 45 km in 2 days were recorded in male feral cats and movement into the baited zone occurred within 2 days of baiting. Movement patterns of radio-collared animals and inferred bait detection distances were used to suggest optimum baiting densities of ~30 baits per km2 for feral cats and 5 per km2 for foxes. Feral cats exhibited much higher intra-specific variation in activity patterns and home-range size than did foxes, rendering them a potentially difficult species to control by a single method. Control of cats and foxes in arid Australia should target habitats with thick vegetation cover and aerial baiting should ideally occur over areas of several thousand square kilometres because of large home ranges and long-range movements increasing the chance of fast reinvasion. The use of temporary focal points suggested that it may take several days or even weeks for a cat to encounter a fixed trap site within their home range, whereas foxes should encounter them more quickly as they move further each day although they have a similar home-range size. Because of high intra-specific variability in activity patterns and home-range size, control of feral cats in inland Australia may be best achieved through a combination of control techniques.

The home-range concept: are traditional estimators still relevant with modern telemetry technology?

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2010.0093 ◽

2010 ◽

Vol 365 (1550) ◽

pp. 2221-2231 ◽

Cited By ~ 268

Author(s):

John G. Kie ◽

Jason Matthiopoulos ◽

John Fieberg ◽

Roger A. Powell ◽

Francesca Cagnacci ◽

...

Keyword(s):

Home Range ◽

New Technologies ◽

Animal Movement ◽

Space Use ◽

Ease Of Use ◽

Home Ranges ◽

Data Intensive ◽

Use Patterns ◽

Location Data ◽

Utilization Distributions

Recent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.

A Pilot Study on Home Range and Habitat Use of Chinese Goral (Naemorhedus Griseus): Exploring GPS Tracking Data in Cliff Landscape by Three Estimation Methods

10.21203/rs.3.rs-597882/v1 ◽

2021 ◽

Author(s):

yang teng ◽

Shupei TANG ◽

lai heda meng ◽

Liji Wu ◽

Zhiqing HAN ◽

...

Keyword(s):

Home Range ◽

Habitat Use ◽

Estimation Methods ◽

Conservation Strategies ◽

Gps Tracking ◽

Tracking Data ◽

Size Estimation ◽

Range Estimation ◽

Lower Altitude ◽

Effective Conservation

Abstract Home range size estimation is a crucial basis for developing effective conservation strategies and provides important insights into animal behavior and ecology. This study aimed at analyzing the home range variations, the influence of altitude in habitat selection, and comparing three methods in home range estimation of Chinese gorals (Naemorhedus griseus) living at a cliff landscape. The results indicated that there were significant differences between the annual home range sizes of individual animals but there was no difference in their seasonal home range sizes based on GPS tracking data of five female Chinese gorals from February 2015 to September 2018. The monthly home ranges decreased dramatically in May, June and July due to birth-giving. Notable seasonal variations were found in the micro-habitats of the Chinese gorals, as reflected by the altitude they inhabit, with higher altitude habitats used in spring and lower altitude habitats used in winter. Additionally, the altitude of monthly habitats was lowest in January, which may indicate an adaptation to low air temperature. We also found differences between estimation methods, namely minimum convex polygon (MCP), kernel density estimation (KDE) and α-local convex hull (α-LoCoH), with seasonal home range sizes derived from α-LoCoH being substantially smaller than those derived from MCP and KDE. In conclusion, our findings filled the gaps in home range study for this endangered species and contributed to effective conservation strategies. Considerations shall have to be given to the variations in home range estimation caused by different methods when dealing with rugged habitats, so as to make sure that any interpretation concerning the habitat use of the targeted species made on basis of such results would be meaningful and valid.

ctmmweb: A graphical user interface for autocorrelation-informed home range estimation

10.1101/2020.05.11.087932 ◽

2020 ◽

Cited By ~ 2

Author(s):

Justin M. Calabrese ◽

Christen H. Fleming ◽

Michael J. Noonan ◽

Xianghui Dong

Keyword(s):

Home Range ◽

Kernel Density ◽

R Package ◽

Home Ranges ◽

Tracking Data ◽

Sampled Data ◽

Convex Polygons ◽

Range Estimation ◽

Empirical Reality ◽

Range Overlap

ABSTRACTEstimating animal home ranges is a primary purpose of collecting tracking data. All conventional home range estimators in widespread usage, including minimum convex polygons and kernel density estimators, assume independently sampled data. In stark contrast, modern GPS animal tracking datasets are almost always strongly autocorrelated. This incongruence between estimator assumptions and empirical reality leads to systematically underestimated home ranges. Autocorrelated kernel density estimation (AKDE) resolves this conflict by modeling the observed autocorrelation structure of tracking data during home range estimation, and has been shown to perform accurately across a broad range of tracking datasets. However, compared to conventional estimators, AKDE requires additional modeling steps and has heretofore only been accessible via the command-line ctmm R package. Here, we introduce ctmmweb, which provides a point-and-click graphical interface to ctmm, and streamlines AKDE, its prerequisite autocorrelation modeling steps, and a number of additional movement analyses. We demonstrate ctmmweb’s capabilities, including AKDE home range estimation and subsequent home range overlap analysis, on a dataset of four jaguars from the Brazilian Pantanal. We intend ctmmweb to open AKDE and related autocorrelation-explicit analyses to a wider audience of wildlife and conservation professionals.

A Pilot Study on Home Range and Habitat Use of Chinese Goral (Naemorhedus Griseus): Exploring GPS Tracking Data in Cliff Landscape by Three Estimation Methods

10.21203/rs.3.rs-597882/v2 ◽

2021 ◽

Author(s):

Yang Teng ◽

Shupei TANG ◽

Dalai Menghe ◽

Liji Wu ◽

Zhiqing HAN ◽

...

Keyword(s):

Home Range ◽

Habitat Use ◽

Estimation Methods ◽

Conservation Strategies ◽

Gps Tracking ◽

Tracking Data ◽

Size Estimation ◽

Range Estimation ◽

Lower Altitude ◽

Effective Conservation

Abstract Home range size estimation is a crucial basis for developing effective conservation strategies and provides important insights into animal behavior and ecology. This study aimed at analyzing the home range variations, the influence of altitude in habitat selection, and comparing three methods in home range estimation of Chinese gorals (Naemorhedus griseus) living at a cliff landscape. The results indicated that there were significant differences between the annual home range sizes of individual animals but there was no difference in their seasonal home range sizes based on GPS tracking data of five female Chinese gorals from February 2015 to September 2018. The monthly home ranges decreased dramatically in May, June and July due to birth-giving. Notable seasonal variations were found in the micro-habitats of the Chinese gorals, as reflected by the altitude they inhabit, with higher altitude habitats used in spring and lower altitude habitats used in winter. Additionally, the altitude of monthly habitats was lowest in January, which may indicate an adaptation to low air temperature. We also found differences between estimation methods, namely minimum convex polygon (MCP), kernel density estimation (KDE) and α-local convex hull (α-LoCoH), with seasonal home range sizes derived from α-LoCoH being substantially smaller than those derived from MCP and KDE. In conclusion, our findings filled the gaps in home range study for this endangered species and contributed to effective conservation strategies. Considerations shall have to be given to the variations in home range estimation caused by different methods when dealing with rugged habitats, so as to make sure that any interpretation concerning the habitat use of the targeted species made on basis of such results would be meaningful and valid.