Discussion
Using a unique detailed concomitant monitoring of both prey and
predators, we showed that predators adjusted their foraging behaviour to
diel prey distribution patterns (PDPs) and light levels. We found that
while the two predators’ behavioural response to PDPs followed similar
curves, there were interesting differences in response to light levels
that could be explained through the PDPs (e.g. the difference in timing
of effort, period of elevated efficiency and depth of dives). WhileU. aalge dive behaviour was symmetrical around noon, reflecting
the depth distribution of prey, the A. torda efforts rather
reflected an inverted curve of aggregation numbers, and with next to no
dive activity in low light levels despite favourable prey distribution.
The predator’s niche partitioning is therefore most likely a result ofU. aalge adaptations to low light conditions (Regular, Hedd and
Montevecchi, 2011) which allows them to exploit a wider range of PDPs,
both in time and depth, while A. torda appear more dependent on
high light levels overall. However, A. torda ’ ability to forage
efficiently for an extended period throughout the afternoon and dusk
allowed them to meet needs before their efficiency is reduced by late
night light conditions. Despite the species differences in response to
light, both achieved high efficiency under conditions of shallow prey
distributions and intermediate aggregation numbers. Our results
highlight shared strategies in adapting to the dynamic prey landscape
and niche partitioning in ability to utilize different prey
distributions.
1 Predator niche
partitioning
Despite their dive capacity (Chimienti et al. , 2017), U.
aalge were most efficient when prey was shallow and/or aggregation
numbers were low, particularly under low-light conditions. This may be
partially explained by the metabolic constraints of longer, deeper
dives, which increase recovery times and thus reduce efficiency of dives
(Walton, Ruxton and Monaghan, 1998). A. torda , on the other hand,
achieved peak efficiency at intermediate prey depths while being more
efficient with the deeper of the utilized depth distributions if
aggregation numbers were low, indicating that high numbers of
aggregations were the main driver for decreased efficiency. This is
reflected by their foraging under low azimuth levels, where both species
reached peak foraging effort and efficiency well before maximum prey
aggregation numbers in the morning, and peaked only after the
aggregation numbers had declined in the afternoon. This, along with the
dive depth responses suggests that foraging under intermediate and
higher number of aggregations during dawn and mornings is likely driven
by a trade-off between shallow depths of prey and suitable light levels,
rather than by targeting intermediate levels of aggregations. U.
aalge in addition tended to dive deeper at higher numbers of
aggregations suggesting they adapted hunting tactics based on the PDPs.
Potentially, U. aalge has dive- (Schneider and Piatt, 1986;
Ponganis, 2015; Chimienti et al. , 2017) and visual (Smith and
Clarke, 2012) capacities that allows them to utilize deeper depths with
less aggregated prey if needed. Particularly interesting was the finding
that in the evenings A. torda foraging effort tended to decrease
before efficiency had reached its peak, likely reflecting a combination
of state-dependent urgency in foraging (Houston and Rosenström, 2024),
lack of predictability of good foraging patches (Bednekoff and Krebs,
1995; Houston and Rosenström, 2024) and the constraints by light
availability. Early afternoon foraging efforts could secure resources
under suboptimal conditions in anticipation of peak efficiency later in
the afternoon, thus avoiding the risk of low-reward, opportunistic
foraging after dark (Houston and Rosenström, 2024) when site-to-site
orientation may be difficult.
Despite both species having the dive capacity needed for all available
depths in the study area (Piatt and Nettleship, 1985), A. torda ceased diving at relatively shallow prey depths as compared to theU. aalge and to A. torda in other systems (Barrettet al. , 1990). This is likely influenced by the poor light
conditions and turbidity in the Baltic Sea (Murray et al. , 2019),
rather than their adaptations regarding pressure at depths (Ponganis,
2015). The predators dove deeper with higher light levels, when prey was
highly aggregated and while depth distribution was high. However, if
there were more aggregations while prey depth was deep, both species
would dive even deeper than before according to the interaction. As
aggregations, particularly in high numbers tended to appear at
relatively shallow depths, in the period of predator tracking, this
response again suggests higher numbers of aggregations were unfavourable
to both predator species, leading to strategies specific to
aggregations. Much of the deviance in bout length was explained by light
levels and prey distributions, where in A. torda bout lengths
increased when there were many aggregations or distribution was deep,
while for U. aalge the increase was by large attained high
numbers of aggregations. It is however not possible to distinguish
whether long bout lengths reflect an increased effort due to favourable
foraging conditions or decreased success rate, and the two scenarios may
not be mutually exclusive. In summary, U. aalge were more
flexible in their utilization of prey distribution patterns through
exploitation of a broader range of light levels and depths, and may thus
be more robust to focal changes within a foraging site or range of
colony during breeding.
2 Symmetry and synchrony of
PDPs
The twilight bound aggregation peaks observed were likely due to
aggregations formed during the vertical migration of clupeids (Zwolinskiet al. , 2007; Solberg and Kaartvedt, 2017). The differences in
numbers of aggregations during the morning versus evening (25%
reduction) could be explained by state dependent behaviours (Lima and
Dill, 1990) during diel vertical migration. During the morning descent
phase (<120° azimuth) the fish may have foraged all night
(Nilsson et al. , 2003), and should prioritize energy-saving group
swimming (Weihs, 1973), or even anti-predation behaviour by
aggregating(Brock and Riffenburgh, 1960). This is perhaps particularly
true for planktivores that remains in shallower water during the day
after the vertical migration of zooplankton to deeper depths (Bollenset al. , 2011). The lower aggregation peak in the afternoon
(>250° azimuth) would then reflect prioritized foraging (Lima
and Dill, 1990), an activity which is likely to start already during the
ascent (See Appendix A4). The asynchrony between aggregation and depth
migration supports this interpretation, since numbers of aggregations
started before the descent and decreased as vertical migration was
finalized. Interestingly, this asymmetry created a temporal window of
elevated foraging conditions in the late afternoon and dusk for
predators that perform better with low levels of aggregations and better
visual conditions. Increased foraging activity in afternoon/dusk (i.e.
vespertine preference) compared to dawn (i.e. matutinal preference), as
seen here in A. torda, is found in a range of crepuscular taxa
(Gupta et al. , 2023). Though this has been explained largely by
state dependency, cost of movement and risk of starvation, this study
identify nuanced spatiotemporal prey behaviour as an underlying
mechanism. Previous studies have shown how U. aalge , utilises
prey distributions at different hierarchical scales, but were unable to
determine the dynamics between prey distribution and predator foraging
site at fine scale (<3km resolution) (Fauchald, Erikstad and
Skarsfjord, 2000). We here present an alternative approach to
disentangle such small-scale predator-prey dynamics with high temporal
resolution.
As prey aggregation patterns were highly variable throughout the study
period (Appendix A4), seeing an adaptation to handling a specific level
of aggregations would be impractical for the predator unless the pattern
impacted fecundity drastically. This may partially explain why
aggregations seem to have a higher impact on foraging efficiency, effort
and strategy across predator species. It should be noted that the number
of aggregations predicted on the birds data were modest compared to the
average estimates from the initial prey distribution models, which again
was modest compared to some of the aggregation patterns recorded. This
is due to most bird tracking being performed later in summer when
aggregations activity in prey were lower. It has been unclear whether
aggregations serve an advantage (e.g. by prey detectability) or a
disadvantage (e.g. reduced prey catchability by confusion effect) to
diving predators, and in particular small seabirds with limited dive
capacity such as the alcids (Lett et al. , 2014; Thiebaultet al. , 2016). Our study strongly suggest hunting under high
aggregation is a focal disadvantage for both species, but our
measurement for aggregations here were highly simplistic. Future studies
should aim to take more complex aggregation characteristics (i.e.
density) and presence-absence into account. Further, as we cannot
distinguish the prey species or age/size classes in our prey data, the
effects could be prey type related.
3 Conclusion
Light is a major driving factor of the predator niche differentiation,
where U. aalge have a better ability to hunt in low light
conditions as compared to A. torda . We were able to explain the
higher dive efficiency and effort by predators during dawn and
afternoon/dusk through temporal nuances in prey distribution patterns.
Both predators performed better under shallow prey distribution with
intermediate numbers of aggregations, but with differences in ability to
forage under low-light conditions segregating them in timing of foraging
and depth in the water column. U. aalge showed ability to utilize
a wider range of light and prey distribution patterns than A.
torda. The asymmetry in predator’s behaviour around solar angle (i.e.
azimuth) was explained by PDPs both directly and indirectly through
timing by light. While the deep diving U. aalge utilized the
light levels during prey’s vertical migrations more, the A. torda was more affected by dynamics in the numbers of aggregations. The wide
range of conditions utilized by U. aalge could give them an
advantage under changes in PDPs, and perhaps even prey type, by season,
or population impacts like fisheries and climate change, buffering them
for their limitations in flight adaptation as compared to A.
torda .