CONDUCTA PROHIBIDA La conducta operada por el sujeto activo consiste en “matar a otro”, lo que significa ocasionar la muerte de su

In the monthly visual and acoustic models, there was considerable variation among the best models for each month. Consequently, the distribution and habitat preferences of harbour porpoises were assessed at a more coarse temporal scale to investigate whether more consistent patterns exist within the year. The results of this study indicated that, at this temporal scale, harbour porpoise distribution was relatively constant throughout the year. The best visual seasonal models and the best acoustic seasonal models were very similar, with a suite of covariates retained in each model, with some small variations in best model structures. In the best S1 and S2 visual and acoustic models, sea state, boat speed, water depth, seabed slope and distance to land or position relative to tidal amplitude were all retained. The impact of sea state and boat speed has been discussed in §4.4.2.

Slope has been important in influencing cetacean distribution in a number of studies (Acevedo and Burkhart 1998; Heinrich 2006; Tynan et al. 2005), probably because it serves to increase productivity and/or prey availability by impacting the movements of currents (Inall et al. 2009), providing an anchor point for eddies, rips and jets which have the potential to enhance prey densities making them important foraging spots (Mooers et al. 1979; Wakefield et al. 2009; Zamon 2003). As in Chapter 3, regions with maximum water depths between 50 – 150 m were where the highest detection rates were observed. Depth has been important in a number of

studies of harbour porpoise distribution and habitat usage. The relationship with depth observed in this study has been recorded in a number of other studies in this region (Embling et al. 2005; Goodwin and Speedie 2008; MacLeod et al. 2007; Marubini et al. 2009)(it should be noted that the Embling et al. (2005) work used some of the data used in this study, but with different analytical methods). This consistently observed preference for regions with water depths between 50 and 150 m in a number of models suggests that this preference is particularly important and temporally robust. The relationship between porpoise density and depth could potentially be explained by the availability of prey species in such regions as a number of fish species are known to inhabit a similar range of water depths, e.g. whiting: 40 – 200 m (Persohn et al. 2009); cod: 30 – 200 m (Santos et al. 2005) and sandeels: 30 – 120 m (Wright et al. 2000). When comparing the covariate relationships between the models built using the S1 and S2 datasets, the majority of relationships were the same in both models. The exception in the visual models was the position relative to tidal range, which was retained in both the S1 and S2 models, but the occurrence of peak detection rates varied between these periods. In April – June, peak sighting rates were observed during periods of low tidal amplitude, i.e. neap tidal periods, and a second peak during periods close to full spring tides. Conversely, in the July – September model, detection rates were low during neap tides, but increased when tidal ranges were moderate, peaking around spring tides. It is not clear why porpoise sightings would be influenced by proximity to spring or neap tides or why there are two distinct patterns observed between S1 and S2. Variation in detection rates with position in the spring-neaps cycle has been observed in other studies of harbour porpoises and there is no clear consensus in the literature of its functional signficance. Embling et al. (2010), in an earlier analysis of some of the data used here, observed peak sighting rates during spring tides and attributed this to porpoise being more active during spring tides, perhaps due to vigorous surface foraging activity. Prey are likely to be more concentrated during spring tides than neap tides due to the currents generated by the greater volume of water shifting in the tidal cycle. Conversely, however, studies have observed peak sighting rates during neap tides in the Bay of Fundy, with the explanation being that animals may have been avoiding extreme current speeds (Embling et al. 2010; Gaskin and Watson 1985). However, this may also be explained by a probable increase in sea state when tidal velocities are high which will likely impact visual detection (Palka 1996). Another possible explanation is that the variation observed is a response to specific prey movements. A number of fish species have been documented to use ‘tidal-stream transport’ to move around (Weihs 1978). Furthermore, some prey species of harbour porpoise may become more available to be preyed upon depending on the state of tide (Arnold 1981; Gibson 1978). It is not clear whether porpoise

behaviour is different during the spring, neap or intermediate tidal phases or how the behaviour of animals will affect their detectability but these subjects need to be further investigated in order to understand the observed patterns. Additionally, it is noteworthy that this covariate was not retained in the acoustic models, which perhaps indicates, that whatever factors are impacting harbour porpoise distribution or detection in the visual data, are not significantly impacting porpoise acoustic behaviour. Foraging sounds (known as ‘buzzes’ (Johnson et al. 2008; Miller et al. 2004)) were not easily detected in the acoustic dataset, though an investigation of the

distribution of buzz detections may yield different results focused on foraging-related habitat preferences.

In the S1 acoustic model, current speed and percentage gravel were significant factors while in S2, these covariates were replaced by spring tidal range. In the April – June model, acoustic detection rates were highest in regions with high (> 0.5 ms-1_{) current speeds. Strong currents are}

known to play an important role in coastal environments - driving tidal eddies and rips and impacting the distribution of piscivorous predators (Mann and Lazier 2006; Zamon 2003), and they were important in a number of cetacean habitat studies (Calderan 2003; Embling et al. 2010; Johnston et al. 2005; Pierpoint 2008). Tidal eddies and rips form when tidal currents flow past headlands, prominent land masses or steep-sided channels creating temporally and spatially predictable changes in plankton distribution which fish populations take advantage of and thus can attract top predators (Wolanski and Hamner 1988; Yen et al. 2004; Yen et al. 2005; Zamon 2003). The inclusion of STR in the best S2 model, is likely to indicate that particular spatial regions were important during S2, as the STR where peak detections rates were observed only exist in the waters around Skye and in the south extent of the study region.

There were some other differences in the best models in S1 and S2. For example, in April – June, distance to land was retained but in the S2 model this was replaced by percentage sand in the sediment. In S1, detection rates decreased steeply from <1 km out to 20 km from land, beyond which detection rates slowly decreased out to the maximum distance from land of >60 km. This suggests a strongly inshore distribution during April - June. It is possible that in this instance, distance to land is a proxy for more biologically meaningful features for example, freshwater input generally decreases as distance from land increases meaning higher salinity water further from shore. Plume fronts (influxes of freshwater meeting seawater masses) are common in inshore regions and lead to increased mixing and so an increase in productivity and aggregation (Mann and Lazier 2006). Capes and headlands can serve as anchor points for fronts, providing potential for increased productivity in the photic zone occurring close to shore,

which could also explain the observed pattern (Wakefield et al. 2009; Yen et al. 2004). The composition of the sediment was retained in July - September visual models as percentage sand was retained in the model. Detection rates were highest in regions with either 0 – 40 % or > 80 % sand. Acoustic detection rates were impacted by sediment composition during S1; the highest rates in regions with between 0 – 50 % gravel in the sediment. A preference for regions with between 40 – 60 % mud (and so sand/gravel making up some proportion of the remaining 40 – 60 %) was observed in an earlier study by Embling (2007), which used some of the data included in this analysis. A number of studies have investigated links between fish species and habitat preferences and found links to certain sediment types. It may be that this peak in harbour porpoise acoustic detections in muddy regions is linked to prey availability. Harbour porpoise diet is poorly understood in west Scotland but they are considered to feed on a wide range of prey species around the UK (Herr et al. 2009; Santos and Pierce 2003; Santos et al. 2005; Santos et al. 2004). Generally, whiting is thought to constitute the bulk of porpoise prey on the west coast of Scotland (Santos et al. 2004) and is known to inhabit muddy sand regions (Santos et al. 2005). Similarly, porpoises have been documented to feed on a number of flatfish species which inhabit predominantly muddy sediment (Herr et al. 2009).