Testing spatial transferability of species distribution models reveals differing habitat preferences for an endangered delphinid (Cephalorhynchus hectori) in Aotearoa, New Zealand.

Species distribution models (SDMs) can be used to predict distributions in novel times or space (termed transferability) and fill knowledge gaps for areas that are data poor. In conservation, this can be used to determine the extent of spatial protection required. To understand how well a model transfers spatially, it needs to be independently tested, using data from novel habitats. Here, we test the transferability of SDMs for Hector's dolphin (Cephalorhynchus hectori), a culturally important (taonga) and endangered, coastal delphinid, endemic to Aotearoa New Zealand. We collected summer distribution data from three populations from 2021 to 2023. Using Generalised Additive Models, we built presence/absence SDMs for each population and validated the predictive ability of the top models (with TSS and AUC). Then, we tested the transferability of each top model by predicting the distribution of the remaining two populations. SDMs for two populations showed useful performance within their respective areas (Banks Peninsula and Otago), but when used to predict the two areas outside the models' source data, performance declined markedly. SDMs from the third area (Timaru) performed poorly, both for prediction within the source area and when transferred spatially. When data for model building were combined from two areas, results were mixed. Model interpolation was better when presence/absence data from Otago, an area of low density, were combined with data from areas of higher density, but was otherwise poor. The overall poor transferability of SDMs suggests that habitat preferences of Hector's dolphins vary between areas. For these dolphins, population-specific distribution data should be used for conservation planning. More generally, we demonstrate that a one model fits all approach is not always suitable. When SDMs are used to predict distribution in data-poor areas an assessment of performance in the new habitat is required, and results should be interpreted with caution.

Escape response kinematics in two species of tropical shark: short escape latencies and high turning performance.

Accelerative manoeuvres, such as fast-starts, are crucial for fish to avoid predation. Escape responses are fast-starts that include fundamental survival traits for prey that experience high predation pressure. However, no previous study has assessed escape performance in neonate tropical sharks. We quantitatively evaluated vulnerability traits of neonate tropical sharks by testing predictions on their fast-start escape performance. We predicted (1) high manoeuvrability, given their high flexibility, but (2) low propulsive locomotion owing to the drag costs associated with pectoral fin extension during escape responses. Further, based on previous work on dogfish, Squalus suckleyi, we predicted (3) long reaction times (as latencies longer than teleosts, >20 ms). We used two-dimensional, high-speed videography analysis of mechano-acoustically stimulated neonate blacktip reef shark, Carcharhinus melanopterus (n=12), and sicklefin lemon shark, Negaprion acutidens (n=8). Both species performed a characteristic C-start double-bend response (i.e. two body bends), but single-bend responses were only observed in N. acutidens. As predicted, neonate sharks showed high manoeuvrability with high turning rates and tight turning radii (3-11% of body length) but low propulsive performance (i.e. speed, acceleration and velocity) when compared with similar-sized teleosts and S. suckleyi. Contrary to expectations, escape latencies were <20 ms in both species, suggesting that the neurophysiological system of sharks when reacting to a predatory attack may not be limited to long response times. These results provide a quantitative assessment of survival traits in neonate tropical sharks that will be crucial for future studies that consider the vulnerability of these sharks to predation.

Impact of pile-driving on Hector's dolphin in Lyttelton Harbour, New Zealand.

Several dolphin species occur close inshore and in harbours, where underwater noise generated by pile-driving used in wharf construction may constitute an important impact. Such impacts are likely to be greatest on species such as the endangered Hector's dolphin (Cephalorhynchus hectori), which has small home ranges and uses this habitat type routinely. Using automated echolocation detectors in Lyttelton Harbour (New Zealand), we studied the distribution of Hector's dolphins using a gradient sampling design over 92 days within which pile-driving occurred on 46 days. During piling operations, dolphin positive minutes per day decreased at the detector closest to the piling but increased at the mid-harbour detector. Finer-grained analyses showed that close to the piling operation, detections decreased with increasing sound exposure level, that longer piling events were associated with longer reductions in detections, and that effects were long-lasting - detection rates took up to 83 h to return to pre-piling levels.

Quantitative analysis of the acoustic repertoire of southern right whales in New Zealand.

Quantitatively describing the acoustic repertoire of a species is important for establishing effective passive acoustic monitoring programs and developing automated call detectors. This process is particularly important when the study site is remote and visual surveys are not cost effective. Little is known about the vocal behavior of southern right whales (Eubalaena australis) in New Zealand. The aim of this study was to describe and quantify their entire vocal repertoire on calving grounds in the sub-Antarctic Auckland Islands. Over three austral winters (2010-2012), 4349 calls were recorded, measured, and classified into 10 call types. The most frequently observed types were pulsive, upcall, and tonal low vocalizations. A long tonal low call (≤15.5 s duration) and a very high call (peak frequency ∼750 Hz) were described for the first time. Random Forest multivariate analysis of 28 measured variables was used to classify calls with a high degree of accuracy (82%). The most important variables for classification were maximum ceiling frequency, number of inflection points, duration, and the difference between the start and end frequency. This classification system proved to be a repeatable, fast, and objective method for categorising right whale calls and shows promise for other vocal taxa.