The time frame of home‐range studies: from function to utilization

Péron, Guillaume

doi:10.1111/brv.12545

Cited by 17 publications

(20 citation statements)

References 118 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it can be challenging to catch and release a large number of GPS-fitted duikers, and, because duikers live in shady undergrowth and groom themselves quite vigorously, the GPS devices would need to be battery-powered (vs. solar powered). Given the small weight of duikers, and therefore the small allowable weight of the battery, the tracking duration would therefore be severely limited, which is a known factor of bias in home range studies [59].…”

Section: Brief Overview Of the Alternatives To Distance Samplingmentioning

confidence: 99%

Distance sampling of duikers in the rainforest: Dealing with transect avoidance

Bonenfant¹,

Péron²

2020

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Bushmeat is a major source of protein and income in tropical regions but is often over-harvested. A better monitoring of bushmeat stocks could help achieve sustainability. We used a combination of simulations and transect survey data collected from blue duikers (Philantomba monticola) in the Lomako wildlife reserve, Democratic Republic of the Congo, to investigate the use of transect-based distance sampling to monitor bushmeat stocks. The comparison of dung piles and direct observations of duikers evidenced that animals avoided both the transects in the absence of observers, and the observers themselves. This type of behavioural response appeared common in a literature survey. It causes a negative bias in the estimates of population densities from the standard distance sampling methodology. This negative bias would lead to over-pessimistic predictions of population viability, especially if the behavioural response is more intense in the locations where the animals are hunted. In turn, this would lead to excessively conservative management recommendations. To correct for the effect of the behavioural response of the animals to either the transects or the observers, we recommend recording both the forward and perpendicular distances to the observers (2D distance sampling), not just the perpendicular distance. We also recommend multiple-observer protocols. As a cautionary note, we also demonstrate a scenario where the intensity of the behavioural response is too high to reliably estimate the abundance of the population. As a perspective, we outline the general principles of a local stakeholder-based program combining distance sampling with less intensive types of ecological indicators to monitor wildlife populations.

show abstract

Section: Brief Overview Of the Alternatives To Distance Samplingmentioning

confidence: 99%

Distance sampling of duikers in the rainforest: Dealing with transect avoidance

Bonenfant¹,

Péron²

2020

PLoS ONE

Self Cite

View full text Add to dashboard Cite

show abstract

“…With highly dispersed resources, interstitial patches connecting food plots occur in the habitat matrix. This leads to increased exploitation costs for individuals, hence to a need for larger home ranges (Péron, 2019). While a home range with highly dispersed food patches can still be perceived by an individual as being of high quality (Mitchell and Powell, 2008), the expected relationship between classic estimates of the size of a home range (Laver and Kelly, 2008) and resources within the home range would appear negative.…”

Section: Introductionmentioning

confidence: 99%

“…Studies performed across species have long pointed out that the sizes of home ranges should also vary with home range overlap among individuals (Jetz et al, 2004;Péron, 2019), and then according to the average group size typical of a species (Damuth, 1981;Mcloughlin et al, 2000). Hence, the size of an individual's home range for a given resource availability should be larger in group-living individuals than in solitary individuals.…”

Section: Introductionmentioning

confidence: 99%

“…Yet, to map the determinants of the sizes of home ranges among individuals across species, methodological questions arise about how the sizes of home ranges are estimated from location data, and how environmental variables are measured (Nilsen et al, 2005). These are not trivial issues as attested by the substantial literature focusing on the meaning and definition of a home range (Kie et al, 2010;Fieberg and Börger, 2012;Powell and Mitchell, 2012;Péron, 2019), as well as on statistical methods to estimate not only the sizes of home ranges (Börger et al, 2006a;Kie et al, 2010;Noonan et al, 2019;Péron, 2019) but also resource availability (from the field, Flombaum and Sala, 2007;Redjadj et al, 2012; or remotely, Pettorelli et al, 2005Pettorelli et al, , 2006Garroutte et al, 2016; and more specifically, the edible portion of the biomass, Duparc et al, 2020) and landscape heterogeneity (Sundell- Turner and Rodewald, 2008).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Systematic Review of Within-Population Variation in the Size of Home Range Across Ungulates: What Do We Know After 50 Years of Telemetry Studies?

et al. 2021

View full text Add to dashboard Cite

Studying the factors determining the sizes of home ranges, based on body mass, feeding style, and sociality level, is a long-standing goal at the intersection of ecology and evolution. Yet, how species-specific life history traits interact with different components of the landscape to shape differences in individual home ranges at within-population level has received much less attention. Here, we review the empirical literature on ungulates to map our knowledge of the relative effects of the key environmental drivers (resource availability, landscape heterogeneity, lethal and non-lethal risks) on the sizes of individual home ranges within a population and assess whether species' characteristics (body mass, diet, and social structure), account for observed variation in the responses of the sizes of individual home ranges to local environmental drivers. Estimating the sizes of home ranges and measuring environmental variables raise a number of methodological issues, which complicate the comparison of empirical studies. Still, from an ecological point of view, we showed that (1) a majority of papers (75%) supported the habitat productivity hypothesis, (2) the support for the influence of landscape heterogeneity was less pervasive across studies, (3) the response of cattle-type to variation in food availability was stronger than the response of moose-type, and (4) species-specific body mass or sociality level had no detectable effect on the level of support to the biological hypotheses. To our surprise, our systematic review revealed a dearth of studies focusing on the ecological drivers of the variation in the sizes of individual home ranges (only about 1% of articles that dealt with home ranges), especially in the later decade where more focus has been devoted to movement. We encourage researchers to continue providing such results with sufficient sample sizes and robust methodologies, as we still need to fully understand the link between environmental drivers and individual space use while accounting for life-history constraints.

show abstract

“…To properly inform desperately needed conservation actions (Gibbons et al, 2000;Roll et al, 2017), we 56 must tailor our methodologies to the peculiarities of reptile movement (Péron, 2019) -otherwise we risk 57 designing suboptimal solutions. We must assess the utility of newer methods designed for mammals, before 58 applying them to reptiles (Silva, Crane, Suwanwaree, Strine, Goode, 2018).…”

Section: Introduction 39mentioning

confidence: 99%

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

Silva

Crane

Marshall

et al. 2020

Preprint

View full text Add to dashboard Cite

11Animal movement, expressed through home ranges, can offer insights into spatial and habitat requirements. 12 However, home range estimation methods vary, directly impacting conclusions. Recent technological 13 advances in animal tracking (GPS and satellite tags), have enabled new methods for home range estimation, 14 but so far have primarily targeted mammal and avian movement patterns. Most reptile home range studies 15 only make use of two older estimation methods: Minimum Convex Polygons (MCP) and Kernel Density 16 Estimators (KDE), particularly with the Least Squares Cross Validation (LSCV) and reference (href) 17 bandwidth selection algorithms. The unique characteristics of reptile movement patterns (e.g. low 18 movement frequency, long stop-over periods), prompt an investigation into whether newer movement-19 based methods -such as dynamic Brownian Bridge Movement Models (dBBMMs)-are applicable to Very 20High Frequency (VHF) radio-telemetry tracking data. To assess home range estimation methods for reptile 21 telemetry data, we simulated animal movement data for three archetypical reptile species: a highly mobile 22 active hunter, an ambush predator with long-distance moves and long-term sheltering periods, and an 23 ambush predator with short-distance moves and short-term sheltering periods. We compared traditionally 24 used home range estimators, MCP and KDE, with dBBMMs, across eight feasible VHF field sampling 25 regimes for reptiles, varying from one data point every four daylight hours, to once per month. Although 26 originally designed for GPS tracking studies, we found that dBBMMs outperformed MCPs and KDE href 27 across all tracking regimes, with only KDE LSCV performing comparably at some higher-frequency 28 sampling regimes. The performance of the LSCV algorithm significantly declined with lower-tracking-29 frequency regimes, whereas dBBMMs error rates remained more stable. We recommend dBBMMs as a 30 viable alternative to MCP and KDE methods for reptile VHF telemetry data: it works under contemporary 31 tracking protocols and provides more stable estimates, improving comparisons across regimes, individuals 32 and species. 33 2 34 Keywords: 35 Reptile, home range, simulation, spatial ecology, minimum convex polygon, kernel density, dynamic 36 Brownian Bridge Movement Models, snake, lizard, squamate, tortoise 37 38 3

show abstract

The time frame of home‐range studies: from function to utilization

Cited by 17 publications

References 118 publications

Distance sampling of duikers in the rainforest: Dealing with transect avoidance

Distance sampling of duikers in the rainforest: Dealing with transect avoidance

A Systematic Review of Within-Population Variation in the Size of Home Range Across Ungulates: What Do We Know After 50 Years of Telemetry Studies?

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

Contact Info

Product

Resources

About