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Many species are restricted to a marginal or suboptimal fraction of their historical range due to anthropogenic impacts, making it hard to interpret their ecological preferences from modern-day data alone. However, inferring past ecological states is limited by the availability of robust data and biases in historical archives, posing a challenge for policy makers . To highlight how historical records can be used to understand the ecological requirements of threatened species and inform conservation, we investigated sperm whale (Physeter macrocephalus) distribution in the Western Indian Ocean. We assessed differences in information content and habitat suitability predictions based on whale occurrence data from Yankee whaling logs (1792–1912) and from modern cetacean surveys (1995–2020). We built maximum entropy habitat suitability models containing static (bathymetry-derived) variables to compare models comprising historical-only and modern-only data. Using both historical and modern habitat suitability predictions we assessed marine protected area (MPA) placement by contrasting suitability in- and outside MPAs. The historical model predicted high habitat suitability in shelf and coastal regions near continents and islands, whereas the modern model predicted a less coastal distribution with high habitat suitability more restricted to areas of steep topography. The proportion of high habitat suitability inside versus outside MPAs was higher when applying the historical predictions than the modern predictions, suggesting that different marine spatial planning optimums can be reached from either data sources. Moreover, differences in relative habitat suitability predictions between eras were consistent with the historical depletion of sperm whales from coastal regions, which were easily accessed and targeted by whalers, resulting in a modern distribution limited more to steep continental margins and remote oceanic ridges. The use of historical data can provide important new insights and, through cautious interpretation, inform conservation planning and policy, for example, by identifying refugee species and regions of anticipated population recovery., Muchas especies están restringidas a una fracción marginal o subóptima de su área de distribución histórica debido a impactos antropogénicos. Esto dificulta interpretar sus preferencias ecológicas con sólo usar los datos actuales. Sin embargo, la inferencia de estados ecológicos pasados está limitada a la disponibilidad de datos sólidos y a los sesgos de los archivos históricos, lo que plantea un reto para la conservación y los responsables de las políticas. Analizamos la distribución del cachalote (Physeter macrocephalus) en el Océano Índico occidental para resaltar cómo pueden utilizarse los registros históricos para comprender los requisitos ecológicos de las especies amenazadas y direccionar su conservación. Evaluamos las diferencias en el contenido de la información y las predicciones de idoneidad del hábitat basadas en los datos de presencia de ballenas de los registros balleneros Yanquis (1792-1912) y de los estudios actuales sobre cetáceos (1995-2020). Construimos modelos de idoneidad de hábitat con máxima entropía que incluían variables estáticas (derivadas de la batimetría) para comparar los modelos que abarcan datos históricos y actuales. Evaluamos la ubicación de las áreas marinas protegidas (AMP) contrastando las predicciones dentro y fuera de ellas con los modelos históricos y actuales de la idoneidad del hábitat. El modelo histórico predijo una alta idoneidad del hábitat en las regiones costeras y de la plataforma continental cercanas a los continentes e islas, mientras que el modelo moderno predijo una distribución menos costera con una alta idoneidad del hábitat más restringida a las zonas de topografía escarpada. La proporción de hábitats de alta idoneidad dentro y fuera de las AMP fue mayor con la aplicación de las predicciones históricas que con la de las modernas, lo que sugiere que se pueden alcanzar diferentes niveles óptimos de ordenación del espacio marino a partir de ambas fuentes de datos. Además, las diferencias entre los periodos en las predicciones relacionadas con la idoneidad del hábitat fueron coherentes con la reducción histórica de los cachalotes en las regiones costeras, las cuales eran fácilmente accesibles para los balleneros, lo que resultó en una distribución actual más limitada a los márgenes continentales escarpados y a las crestas oceánicas remotas. El uso de datos históricos puede aportar nuevos e importantes conocimientos e informar, mediante una interpretación prudente, a la planificación y la política de conservación; por ejemplo, con la identificación de especies refugiadas y regiones de recuperación poblacional.

In the central Indian Ocean, humpback whales (Megaptera novaeangliae) are rare. Records from southern India, Sri Lanka, Maldives and the Chagos Archipelago (n=67) were compiled and show a bimodal pattern of seasonal occurrence. Those occurring during the northern winter (December to April) are known to belong to the Arabian Sea humpback whale population. There have been no humpback whales recorded in Maldives during the northern winter since 2001, suggesting a possible range contraction for the Arabian Sea humpback whale population. Humpback whales occurring during the southern winter (June to October) are assumed to belong to the southwest Indian Ocean population (IWC breeding stock C). In this case, numbers of opportunistic sightings are increasing and the population appears to be spreading northwards as it recovers from commercial whaling, with several recent southern winter records from as far north as 5°N in northern Maldives and southern Sri Lanka. For this southern hemisphere population, calves are first seen in August, with numbers of calves increasing in September and October. For both populations, interactions with regional fisheries, particularly pelagic gillnetting, may be a major cause of mortality.

An unusual sighting of a juvenile southern elephant seal (Mirounga leonina), outside its typical range, was recorded off the southern coast of Sri Lanka between 20th November and 20th December 2019. The individual, a male as confirmed by the presence of a prepuce, underwent a catastrophic moult during this 1 month period, following which no further observations were recorded and so it was assumed it returned to sea. This represents the first confirmed sighting of a southern elephant seal, and indeed a phocid, in Sri Lankan waters.

Aim Human activities are creating conservation challenges for cetaceans. Spatially explicit risk assessments can be used to address these challenges, but require species distribution data, which are limited for many cetacean species. This study explores methods to overcome this limitation. Blue whales (Balaenoptera musculus) are used as a case study because they are an example of a species that have well-defined habitat and are subject to anthropogenic threats. Location Eastern Pacific Ocean, including the California Current (CC) and eastern tropical Pacific (ETP), and northern Indian Ocean (NIO). Methods We used 12 years of survey data (377 blue whale sightings and c. 225,400 km of effort) collected in the CC and ETP to assess the transferability of blue whale habitat models. We used the models built with CC and ETP data to create predictions of blue whale distributions in the data-poor NIO because key aspects of blue whale ecology are expected to be similar in these ecosystems. Results We found that the ecosystem-specific blue whale models performed well in their respective ecosystems, but were not transferable. For example, models built with CC data could accurately predict distributions in the CC, but could not accurately predict distributions in the ETP. However, the accuracy of models built with combined CC and ETP data was similar to the accuracy of the ecosystem-specific models in both ecosystems. Our predictions of blue whale habitat in the NIO from the models built with combined CC and ETP data compare favourably to hypotheses about NIO blue whale distributions, provide new insights into blue whale habitat, and can be used to prioritize research and monitoring efforts. Main conclusions Predicting cetacean distributions in data-poor ecosystems using habitat models built with data from multiple ecosystems is potentially a powerful marine conservation tool and should be examined for other species and regions.

An unusually coloured, small baleen whale was documented off the southern coast of Sri Lanka in February 2017 during routine field surveys. Based on five distinct morphological characteristics including jaw asymmetry, presence of a prominent central rostral ridge, blaze on right side, asymmetrical chevron on left and right sides and a strongly falcate dorsal fin the individual was positively identified as an Omura’s whale (Balaenoptera omurai). This discovery represents the first confirmed sighting of Omura’s whale in Sri Lankan and therefore central Northern Indian Ocean waters.

Surfacing behaviour and dive characteristics were quantified from focal follows of individual blue whales between January–March 2012 and 2013. During this period individual whales were followed from small boats to observe their surfacing patterns and breathing behaviour. Data on time at first surface, length of surface interval, number of blows, final dive time and whether or not the whale ‘fluked up’ before a deep dive were recorded. A step-wise modelling approach was used to estimate a number of surfacing characteristics: mean Inter-Breath Interval (IBI), bout duration and the number of surfacings in a bout. First, dives were classified as either surface dives or deep dives based on the occurrence of arching or fluking behaviour at the surface prior to a deep dive. The mean IBI of surface dives was 17.6 s (SD = 26.14) and for deep dives, 640.3 s (SD = 214.38). To account for temporal dependence between dive types, a first-order Markov chain was used to estimate the transition probability between dive types. Time series of dive types were then simulated, using Monte Carlo methods, while accounting for heterogeneity in IBI of the different dive types. The mean IBI of blue whales in Sri Lanka, obtained from the Monte Carlo methods, was 84.7 s (SD = 11.17). The mean bout duration was 145 s (SD = 28.31), with the mean number of breaths per surface bout being 9.3 (SD = 1.43). Whales also lifted their tail flukes out of the water on 55% of terminal dives, which is considerably more frequent than elsewhere in the world. These results significantly advance our understanding of blue whales in Sri Lankan waters. More specifically, this information is essential for the calculation of precise abundance estimates as it informs the detection probability parameters for line transect surveys. In this way it will help formulate better management decisions related to the conservation of this population.

Despite the popularity of marine protected areas (MPAs) as a management tool, increasing evidence shows that many fail to achieve conservation objectives. Although several MPAs exist in Sri Lanka, most are not managed, and resource extraction and habitat degradation continue unabated. At present, the declaration and management of MPAs is carried out without adequate consideration of the ecology, socioeconomic realities, or long-term management sustainability. Managers have focused more toward the creation of new legislation and protected areas rather than ensuring the implementation of existing regulations and management of existing protected areas. Poor coordination and a lack of serious political will have also hindered successful resource management. As in other developing countries, MPA managers have to contend with coastal communities that are directly dependant on marine resources for their subsistence. This often makes it unfeasible to exclude resource users, and MPAs have failed to attract necessary government support because many politicians are partial toward the immediate needs of local communities for both economic and political reasons. A more integrated approach, and decisions based on the analysis of all relevant criteria combined with a concerted and genuine effort toward implementing strategies and achieving predetermined targets, is needed for effective management of MPAs and the sustainable use of marine resources in Sri Lanka.

Fish orient by using a memorized map of their surroundings and, as they live in aquatic environments, this map must be three dimensional. Studies have shown that fish are able to encode horizontal information; however, we have little information about the cues that are learnt and remembered in the vertical axis. We used the blind Mexican cave fish, Astyanax fasciatus, to test whether fish can orient in the vertical axis and whether they use hydrostatic pressure to do so. After learning the cues associated with a specific height in the aquarium (evident by a reduction in swimming speed), the fish showed significant dishabituation (their swimming speed increased) when moved vertically upwards. When we controlled for the increase in light intensity from the bottom to the top of the tank the effect persisted, indicating that the most likely cue used by the fish to orient vertically was hydrostatic pressure. A post hoc experiment revealed that the change in swimming speed in response to altered light levels probably represents a change in the level of activity rather than an orientational response. This may define a photokinetic mechanism which operates in conjunction with a negatively phototactic response (revealed in previous experiments) by which the fish orient away from higher light levels and swim faster as light levels increase. This would result in the fish spending more time in lower light levels and would prevent the fish exiting the cave. © 2005 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.