Hidden semi‐Markov models reveal multiphasic movement of the endangered Florida panther

Summary1. Due to the substantial progress in tracking technology, recent years have seen an explosion in the amount of movement data being collected. This has led to a huge demand for statistical tools that allow ecologists to draw meaningful inference from large tracking data sets. 2. The class of hidden Markov models (HMMs) matches the intuitive understanding that animal movement is driven by underlying behavioural modes and has proven to be very useful for analysing movement data. For data that involve a regular sampling unit and negligible measurement error, these models usually are sufficiently flexible to capture the complex correlation structure found in movement data, yet are computationally inexpensive compared to alternative methods. 3. The R package moveHMM allows ecologists to process GPS tracking data into series of step lengths and turning angles, and to fit an HMM to these data, allowing, in particular, for the incorporation of environmental covariates. The package includes assessment and visualization tools for the fitted model. 4. We illustrate the use of moveHMM using (simulated) movement of the legendary wild haggis Haggis scoticus. Our findings illustrate the role our software, and movement modelling in general, can play in conservation and management by illuminating environmental constraints.

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“…), panthers (van de Kerk et al . ), woodpeckers (McKellar et al . ) and white sharks (Towner et al .…”

Section: Hidden Markov Models For Animal Movementmentioning

confidence: 99%

“…; van de Kerk et al . ). The HMM approach to movement modelling is part of the wider family of state‐switching models, which focus on the decomposition of the movement process into distinct underlying states.…”

Section: Introductionmentioning

confidence: 97%

moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models

2016

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“…While movement patterns are often used to distinguish active phases from rest, or search behavior from traveling (van Beest & Milner, 2013;Dzialak, Olson, Webb, Harju, & Winstead, 2015), identifying these behavioral states typically relies on more complicated modeling procedures to detect potential underlying mechanisms within behavior identification (Jonsen, Myers, & James, 2006;Kerk et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Search and foraging behaviors from movement data: A comparison of methods

Bennison

Bearhop

Bodey

et al. 2017

Ecology and Evolution

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Search behavior is often used as a proxy for foraging effort within studies of animal movement, despite it being only one part of the foraging process, which also includes prey capture. While methods for validating prey capture exist, many studies rely solely on behavioral annotation of animal movement data to identify search and infer prey capture attempts. However, the degree to which search correlates with prey capture is largely untested. This study applied seven behavioral annotation methods to identify search behavior from GPS tracks of northern gannets (Morus bassanus), and compared outputs to the occurrence of dives recorded by simultaneously deployed time–depth recorders. We tested how behavioral annotation methods vary in their ability to identify search behavior leading to dive events. There was considerable variation in the number of dives occurring within search areas across methods. Hidden Markov models proved to be the most successful, with 81% of all dives occurring within areas identified as search. k‐Means clustering and first passage time had the highest rates of dives occurring outside identified search behavior. First passage time and hidden Markov models had the lowest rates of false positives, identifying fewer search areas with no dives. All behavioral annotation methods had advantages and drawbacks in terms of the complexity of analysis and ability to reflect prey capture events while minimizing the number of false positives and false negatives. We used these results, with consideration of analytical difficulty, to provide advice on the most appropriate methods for use where prey capture behavior is not available. This study highlights a need to critically assess and carefully choose a behavioral annotation method suitable for the research question being addressed, or resulting species management frameworks established.

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“…The modeled data in that study determined that males and females, and females with and without kittens exhibited distinctly different movement patterns, but did not specify if those different movements were within the same habitat types, as suggested by Frakes et al [7], or in different habitat types. Only one female panther carrying a GPS collar gave birth during the van de Kerk et al [23] study. That study also compared the movements of those panthers during wet and dry seasons, defined by Frakes et al [7] as June through…”

Section: Introductionmentioning

confidence: 98%

“…Van de Kerk et al [23] evaluated the movement of 13 Florida panthers using hourly global positioning system (GPS) tracking data and hidden semi-Markov models (HSMM). The modeled data in that study determined that males and females, and females with and without kittens exhibited distinctly different movement patterns, but did not specify if those different movements were within the same habitat types, as suggested by Frakes et al [7], or in different habitat types.…”

Section: Introductionmentioning

confidence: 99%

Management Implications of Aquifer Fractures on Ecosystem and Habitat Suitability for Panthers in Southern Florida

Xu¹,

Bernardes²,

Bacchus³

et al. 2018

GEP

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Our case study analyzed the proximity of previously mapped fractures in the aquifer matrix to 93 Florida panther (Puma concolor coryi) dens mapped from 2007-2016 in south Florida. Dens occurred in five counties (Collier = 77, Dade = 1, Hendry = 9, Lee = 5, and Monroe = 1) and three sub-basins of the Greater Everglades Basin (Big Cypress Swamp = 83, Caloosahatchee = 3, and Everglades = 7). Fractured aquifers occur worldwide, but are not the focus of habitat suitability studies, despite evidence that fractures influence plant species composition and density. Habitat alterations can occur many kilometers from the surface footprint of groundwater alterations in the regional Floridan aquifer system via preferential flow through fractures. Increased natural discharge from and recharge to the aquifer occur at fracture intersections. Greater induced recharge and habitat changes also may occur at fracture intersections. All dens were within 5 km of a previously mapped fracture; 36% and 74% were within 1 km and 2 km, respectively, of those fractures; and 47%, 74%, and 90% of dens were within 2 km, 3.25 km and 5 km, respectively, from the nearest fracture intersection. Results suggest fractures influence the suitability and/or availability of habitat for panther dens, selection of den sites, and availability as well as abundance of high quality prey items essential for the nutritional demands of successfully rearing panther kittens in the wild. We recommend more detailed investigations of: a) vegetation characteristics near dens, b) groundwater alterations and cumulative impacts of those alterations associated with fractures in panther habitat (e.g., altered plant species composition and density), and c) influence of aquifer fractures in all habitats underlain by fractures.

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Hidden semi‐Markov models reveal multiphasic movement of the endangered Florida panther

Cited by 38 publications

References 26 publications

moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models

moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models

Search and foraging behaviors from movement data: A comparison of methods

Management Implications of Aquifer Fractures on Ecosystem and Habitat Suitability for Panthers in Southern Florida

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