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Estimating density of mountain hares using distance sampling: a comparison of daylight visual surveys, night-time thermal imaging and camera traps

Citation

Bedson, Carlos (2021), Estimating density of mountain hares using distance sampling: a comparison of daylight visual surveys, night-time thermal imaging and camera traps, Dryad, Dataset, https://doi.org/10.5061/dryad.3r2280gg0

Abstract

Surveying cryptic, nocturnal animals is logistically challenging. Consequently, density estimates may be imprecise and uncertain. Survey innovations mitigate ecological and observational difficulties contributing to estimation variance. Thus, comparisons of survey techniques are critical to evaluate estimates of abundance. We simultaneously compared three methods for observing mountain hare (Lepus timidus) using Distance sampling to estimate abundance. Daylight visual surveys achieved 41 detections, estimating density at 14.3 hares km-2 (95%CI 6.3–32.5) resulting in the lowest estimate and widest confidence interval. Night-time thermal imaging achieved 206 detections, estimating density at 12.1 hares km-2 (95%CI 7.6–19.4). Thermal imaging captured more observations at furthest distances, and detected larger group sizes. Camera traps achieved 3,705 night-time detections, estimating density at 22.6 hares km-2 (95%CI 17.1–29.9). Between the methods, detections were spatially correlated, although the estimates of density varied. Our results suggest that daylight visual surveys tended to underestimate density, failing to reflect nocturnal activity. Thermal imaging captured nocturnal activity, providing a higher detection rate, but required fine weather. Camera traps captured nocturnal activity, and operated 24/7 throughout harsh weather, but needed careful consideration of empirical assumptions. We discuss the merits and limitations of each method with respect to the estimation of population density in the field.

Methods

Please refer to the manuscript for more information. The data has been prepared for loading in to software distance.  

Usage Notes

META DATA DESCRIPTIONS     

Data are prepared ready for loading in to Software Distance.   

_____DAYLIGHT VISUAL SAMPLING_____

STUDY AREA = HOLME MOSS for all sites

SITE = Sites within the study, numbered 1 through 6 as per the manuscript. 

AREA KM^2 = 8.17KM^2 per site square which sums to 49 KM^2 for the whole area of Holme Moss. 

LINE_LENGTH _KM  = Per site what distance was walked in kilometres.

PERP_DISTANCE_M = Perpendicular distance to the transect line in metres.

CLUSTER_SIZE = How many mountain hares were observed. 

_____NIGHT-TIME THERMAL IMAGING_____

STUDY AREA = HOLME MOSS for all sites

SITE = Sites within the study, numbered 1 through 6 as per the manuscript. 

AREA KM^2 = 8.17KM^2 per site square which sums to 49 KM^2 for the whole area of Holme Moss. 

OBSERVATION POINT = Unique ID for each vantage point.  Some of these received multiple visits so appear several times.

SURVEY_EFFORT = 1 per vantage point.

RADIAL_DISTANCE_M = Radial distance to the mountain hare detection in metres.

CLUSTER_SIZE = How many mountain hares were observed. 

_____CAMERA TRAPS_____

STUDY AREA = HOLME MOSS for all sites

SITE = Sites within the study, numbered 1 through 6 as per the manuscript. 

AREA KM^2 = 8.17KM^2 per site square which sums to 49KM^2 for the whole area of Holme Moss. 

CAM_ID = Unique ID for each camera trap.  These are "point transect labels" for software distance.

SURVEY_EFFORT_SECONDS = Expressed with "1k" i.e. one second is the effort unit.  The value shown is the sum of the effort units for each individual camera i.e. the total number of seconds the camera was deployed for.

RADIAL_DISTANCE_M = Radial distance to the mountain hare detection in metres.

CLUSTER_SIZE = How many mountain hares were observed. 

 

 

Funding

People's Trust for Endangered Species

Hare Preservation Trust

Penny Anderson Associates

Queen's University Belfast

British Mountaineering Council

Action for Hares South West