No room to roam: King Cobras reduce movement in agriculture

Abstract

Background: Studying animal movement provides insights into how animals react to land-use changes. As agriculture expands, we can use animal movement to examine how animals change their behaviour in response. Recent reviews show a tendency for mammalian species to reduce movements in response to increased human landscape modification, but reptile movements have not been as extensively studied.

Methods: We examined movements of a large reptilian predator, the King Cobra (Ophiophagus hannah), in Northeast Thailand. We used a consistent regime of radio telemetry tracking to document movements across protected forest and adjacent agricultural areas. Using dynamic Brownian Bridge Movement Model derived motion variance, Integrated Step-Selection Functions, and metrics of site reuse, we examined how King Cobra movements changed in agricultural areas.

Results: Motion variance values indicated that King Cobra movements increased in forested areas and tended to decrease in agricultural areas. Our Integrated Step-Selection Functions revealed that when moving in agricultural areas King Cobras restricted their movements to remain within vegetated semi-natural areas, often located along the banks of irrigation canals. Site reuse metrics of residency time and number of revisits appeared unaffected by distance to landscape features (forests, semi-natural areas, settlements, water bodies, and roads). Neither motion variance nor reuse metrics were consistently affected by the presence of threatening landscape features (e.g. roads, human settlements), suggesting that King Cobras will remain in close proximity to threats, provided habitat patches are available.

Conclusions: Although King Cobras displayed individual heterogeneity in their response to agricultural landscapes, the overall trend suggested reduced movements when faced with fragmented habitat patches embedded in an otherwise inhospitable land-use matrix. Movement reductions are consistent with findings for mammals and forest specialist species.

Keywords: Elapid; Ophiophagus hannah; Reptile; Site fidelity; Snake; Space-use; Step-selection; Tropical; dBBMM.

Fig. 1

Dynamic Brownian Bridge Movement Model estimates of utilisation distribution contours. Areas displayed with increasing levels of opacity are the 99, 95 and 90% utilisation contours. Black dots show locations. The shaded background area shows the protected core area. Dark central line is the four-lane 304 highway. Bottom right map shows the land-use types in the area

Fig. 2

Motion variance of each individual over their tracking period. Black lines show the motion variance values over time. Grey bars indicate long-term sheltering behaviour (i.e., when the time sheltering was greater than the individual’s mean sheltering time). Blue bars indicate times when the individual was within the protected forested area. Shading shows the three seasons: red = Hot, blue = Wet, yellow = Dry

Fig. 3

Non-metric multidimensional scaling plot. Motion variance values are reflected by the colour of the points, we have rooted these values so value differences are easier to distinguish. Ellipses indicate 95% of points within 100 m of a given landscape feature. a Ellipses highlight points existing within 100 m of forest, semi-natural areas, and roads. b Ellipses highlights points existing within 100 m of water, and settlements

Fig. 4

The coefficients from the integrated step-selection functions per individual. Error bars show the 95% confidence interval. Circles indicated effects included in the top model as determined by ∆ AIC. Positive effects indicate a positive association towards a landscape feature as the distance values were inverted

Fig. 5

A map of land-use illustrating how King Cobra movements are largely occurring within semi-natural areas. Displayed using semi-transparent points, are the locations of King Cobras across the entire study period. Circles = AF017, triangles = AM006, squares = AM015

Fig. 6

The interactive coefficients from the integrated step-selection functions per individual. Error bars show the 95% confidence interval. Circles indicated effects included in the top model as determined by ∆ AIC. log_sl = step length, cos_ta = turning angle. Positive effects indicate a positive interaction between step or angle with a landscape feature as the distance values were inverted