Specialised use of working memory by Portia africana, a spider-eating salticid

Abstract

Using expectancy-violation methods, we investigated the role of working memory in the predatory strategy of Portia africana, a salticid spider from Kenya that preys by preference on other spiders. One of this predator's tactics is to launch opportunistic leaping attacks on to other spiders in their webs. Focussing on this particular tactic, our experiments began with a test spider on a ramp facing a lure (dead prey spider mounted on a cork disc) that could be reached by leaping. After the test spider faced the lure for 30 s, we blocked the test spider's view of the lure by lowering an opaque shutter before the spider leapt. When the shutter was raised 90 s later, either the same lure came into view again (control) or a different lure came into view (experimental: different prey type in same orientation or same prey type in different orientation). We recorded attack frequency (number of test spiders that leapt at the lure) and attack latency (time elapsing between shutter being raised and spiders initiating a leap). Attack latencies in control trials were not significantly different from attack latencies in experimental trials, regardless of whether it was prey type or prey orientation that changed in the experimental trials. However, compared with test spiders in the no-change control trials, significantly fewer test spiders leapt when prey type changed. There was no significant effect on attack frequency when prey orientation changed. These findings suggest that this predator represents prey type independently of prey orientation.

Fig. 1

Prey spiders used in expectancy-violation experiments. (a) Argyrodes sp. 1 facing left with legs up; (b) Argyrodes sp. 1 facing up with legs right; (c) Argyrodes sp. 1 facing right with legs down; (d) Argyrodes sp. 1 facing down with legs left; (e) Argyrodes sp. 1 facing up with legs left; (f) Argyrodes sp. 2 facing left with legs up; (g) Pycnacantha tribulis facing down with legs left; (h) Arachnura scorpionoides (brown morph) facing down with legs left; (i) Arachnura scorpionoides (yellow morph) facing down with legs left; (j) Arachnura scorpionoides (yellow morph) facing up with legs right

Fig. 2

Apparatus (not drawn to scale) used in expectancy-violation experiments. Metal rod and base (not shown) holds ramp in place. Side walls and ceiling not shown. Start of trial: test spider leaves glass tube and walks along ramp towards lure. Cable-release mechanism moves lure forward and back during trial. (a) Apparatus configuration at start of trial, and also when prey was restored later in trial. Lure (situated in front of window) in test spider’s view because shutter is raised. (b) Apparatus configuration during 90-s period in which prey is hidden. Test spider’s view of lure blocked because shutter is lowered. Lure pulled back behind window and removed from pin. Different lure then attached to pin (experimental trials) or same lure re-attached to pin (control trials)

Fig. 3

Portia africana tested with different prey types. Prey orientation constant for each condition. (a) Attack frequencies (percentage of test spiders that leapt at the prey). (b) Attack latencies. Experimental: second prey type different from first prey type. Control: first and second prey types the same. See Table 1 for prey types used in each condition. Total number of test spiders (n) shown above bars in (a). Boxes in (b) show medians and upper and lower quartiles, and whiskers show minimum and maximum values

Fig. 4

Portia africana tested with different prey orientations. Prey type constant for each condition. (a) Attack frequencies (percentage of test spiders that leapt at the prey). (b) Attack latencies. Experimental: second prey’s orientation different from first prey’s orientation. Control: first and second prey’s orientation the same. See Table 2 for prey orientations used in each condition. Total number of test spiders (n) shown above bars in (a). Boxes in (b) show medians and upper and lower quartiles, and whiskers show minimum and maximum values