Using GPS telemetry to validate least-cost modeling of gray squirrel (Sciurus carolinensis) movement within a fragmented landscape

Abstract

In Britain, the population of native red squirrels Sciurus vulgaris has suffered population declines and local extinctions. Interspecific resource competition and disease spread by the invasive gray squirrel Sciurus carolinensis are the main factors behind the decline. Gray squirrels have adapted to the British landscape so efficiently that they are widely distributed. Knowledge on how gray squirrels are using the landscape matrix and being able to predict their movements will aid management. This study is the first to use global positioning system (GPS) collars on wild gray squirrels to accurately record movements and land cover use within the landscape matrix. This data were used to validate Geographical Information System (GIS) least-cost model predictions of movements and provided much needed information on gray squirrel movement pathways and network use. Buffered least-cost paths and least-cost corridors provide predictions of the most probable movements through the landscape and are seen to perform better than the more expansive least-cost networks which include all possible movements. Applying the knowledge and methodologies gained to current gray squirrel expansion areas, such as Scotland and in Italy, will aid in the prediction of potential movement areas and therefore management of the invasive gray squirrel. The methodologies presented in this study could potentially be used in any landscape and on numerous species.

Keywords: Conservation; GIS; corridors; management.

Figure 1

Study site, Lancashire, U.K.

Figure 2

Complete GPS radio collar ready for fitting.

Figure 3

Fitted collar with GPS device at the top and radio transmitter underneath. Note the hessian cone with adjustable neck still to be undone, releasing the squirrel.

Figure 4

Using regression analysis to show a change in gray squirrel landscape feature at 40 m.

Figure 5

Frequency of GPS points recorded in each land cover type within the study site used in chi-square analysis. I/A/A = Improved/Arable and Amenity, R/P/RV/T = Road/Path/Road Verge/Track, ***P < 0.001 in subdivided testing, **P < 0.001, *P < 0.01.

Figure 6

Landscape features that were closest to GPS points used in chi-square analysis. Field edge includes hedgerows, fence rows, and walls, ***P < 0.001 in subdivided testing, **P < 0.001, *P < 0.01.

Figure 7

Study site with least-cost networks and GPS data.

Figure 8

Buffered least-cost paths created from OSMM with additional field edge feature and tree row habitat.

Figure 9

Least-cost corridor identified from OSMM with additional field edge feature and tree row habitats.