Corrigendum: Abundance and Potential Biological Removal of Common Dolphins Subject to Fishery-Impacts in South Australian Waters

Conservation management of wildlife species should be underpinned by knowledge of their distribution and abundance, as well as impacts of human activities on their populations and habitats. Common dolphins (Delphinus delphis) are subject to incidental capture in a range of Australia’s commercial fisheries including gill netting, purse seining and mid-water trawling. The impact these fishery interactions have on common dolphin populations is uncertain, as estimates of abundance are lacking, particularly for the segments of the populations at risk of bycatch and in greater need of protection. Here we used double-observer platform aerial surveys and mark-recapture distance sampling methods to estimate the abundance of common dolphins in 2011 over an area of 42,438 km2 in central South Australia, where incidental mortality of common dolphins due to fisheries bycatch is the highest. We also used the potential biological removal (PBR) method to estimate sustainable levels of human-caused mortality for this segment of the population. The estimated abundance of common dolphins was 21,733 (CV = 0.25; 95% CI = 13,809–34,203) in austral summer/autumn and 26,504 in winter/spring (CV = 0.19; 95% CI = 19,488–36,046). Annual PBR estimates, assuming a conservative maximum population growth rate of Rmax = 0.02 and a recovery factor of Fr = 0.5 for species of unknown conservation status, ranged from 95 (summer/autumn) to 120 dolphins (winter/spring), and from 189 (summer/autumn) to 239 dolphins (winter/spring) with an Rmax = 0.04. Our results indicate that common dolphins are an abundant dolphin species in waters over the central South Australian continental shelf (up to 100 m deep). Based on the 2011 abundance estimates of this species, the highest estimated bycatch of common dolphins (423 mortalities in 2004/05) in the southern Australian region exceeded the precautionary PBR estimates for this population segment. Recent bycatch levels appear to be below PBR estimates, but low observer coverage and underreporting of dolphin mortalities by fishers means that estimates of dolphin bycatch rates are not robust. The effects of cumulative human impacts on common dolphins are not well understood, and thus we recommend a precautionary management approach to manage common dolphin bycatch based on local abundance estimates

Pygmy blue whale movement, distribution and important areas in the Eastern Indian Ocean

This study was conducted as part of AIMS’ North West Shoals to Shore Research Program (NWSSRP) and was supported by Santos as part of the company’s commitment to better understand Western Australia’s marine environment. Hydrophone pressure data from Ocean Bottom Seismometers (OBS) were provided by the CANPASS project, jointly funded by the National Natural Science Foundation of China (NSFC grants 91955210, 41625016), and the China Academy of Science (CAS program GJHZ1776). Instruments were provided by the Australian National instrument pool ANSIR (http://ansir.org.au/). ANSIR, OBS data was also made data available from the Geoscience Australia and Shell. Data was sourced from Australia’s Integrated Marine Observing System (IMOS).Pygmy blue whales in the South-east Indian Ocean migrate from the southern coast of Australia to Indonesia, with a significant part of their migration route passing through areas subject to oil and gas production. This study aimed at improving our understanding of the spatial extent of the distribution, migration and foraging areas, to better inform impact assessment of anthropogenic activities in these regions. Using a combination of passive acoustic monitoring of the NW Australian coast (46 instruments from 2006 to 2019) and satellite telemetry data (22 tag deployments from 2009 to 2021) we quantified the pygmy blue whale distribution and important areas during their northern and southern migration. We show extensive use of slope habitat off Western Australia and only minimal use of shelf habitat, compared to southern Australia where use of the continental shelf and shelf break predominates. In addition, movement behaviour estimated by a state-space model on satellite tag data showed that in general pygmy blue whales off Western Australia were mostly engaged in migration, interspersed with mostly relatively short periods (median = 28hours, range = 2 – 1080hours) of low move persistence (slow movement with high turning angles), which is indicative of foraging. Using the spatial overlap of time and number of whales in area analysis of the satellite tracking data (top 50% of grid cells) with foraging movement behaviour, we quantified the spatial extent of pygmy blue whale high use areas for foraging and migration. We compared these areas to the previously described areas of importance to foraging and migrating whales (Biologically Important Areas; BIAs). In some cases these had good agreement with the most important areas we calculated from our data, but others had only low (5%) to moderate (13%) overlap. Month was the most important variable predicting the number of pygmy blue whale units and number of singers (acting as indices of pygmy blue whale density). Whale density was highest in the southern part of the NW Australian coast and whales were present there between April-June, and November-December, a pattern also confirmed by the satellite tracking data. Available data indicated pygmy blue whales spent up to 124 days in Indonesian waters (34% of annual cycle). Since this area may also be the calving ground for this population, inter-jurisdictional management is necessary to ensure their full protection.Publisher PDFPeer reviewe

The Use of Carcasses for the Analysis of Cetacean Population Genetic Structure: A Comparative Study in Two Dolphin Species

Advances in molecular techniques have enabled the study of genetic diversity and population structure in many different contexts. Studies that assess the genetic structure of cetacean populations often use biopsy samples from free-ranging individuals and tissue samples from stranded animals or individuals that became entangled in fishery or aquaculture equipment. This leads to the question of how representative the location of a stranded or entangled animal is with respect to its natural range, and whether similar results would be obtained when comparing carcass samples with samples from free-ranging individuals in studies of population structure. Here we use tissue samples from carcasses of dolphins that stranded or died as a result of bycatch in South Australia to investigate spatial population structure in two species: coastal bottlenose (Tursiops sp.) and short-beaked common dolphins (Delphinus delphis). We compare these results with those previously obtained from biopsy sampled free-ranging dolphins in the same area to test whether carcass samples yield similar patterns of genetic variability and population structure. Data from dolphin carcasses were gathered using seven microsatellite markers and a fragment of the mitochondrial DNA control region. Analyses based on carcass samples alone failed to detect genetic structure in Tursiops sp., a species previously shown to exhibit restricted dispersal and moderate genetic differentiation across a small spatial scale in this region. However, genetic structure was correctly inferred in D. delphis, a species previously shown to have reduced genetic structure over a similar geographic area. We propose that in the absence of corroborating data, and when population structure is assessed over relatively small spatial scales, the sole use of carcasses may lead to an underestimate of genetic differentiation. This can lead to a failure in identifying management units for conservation. Therefore, this risk should be carefully assessed when planning population genetic studies of cetaceans

Seascape Genetics of a Globally Distributed, Highly Mobile Marine Mammal: The Short-Beaked Common Dolphin (Genus Delphinus)

Identifying which factors shape the distribution of intraspecific genetic diversity is central in evolutionary and conservation biology. In the marine realm, the absence of obvious barriers to dispersal can make this task more difficult. Nevertheless, recent studies have provided valuable insights into which factors may be shaping genetic structure in the world's oceans. These studies were, however, generally conducted on marine organisms with larval dispersal. Here, using a seascape genetics approach, we show that marine productivity and sea surface temperature are correlated with genetic structure in a highly mobile, widely distributed marine mammal species, the short-beaked common dolphin. Isolation by distance also appears to influence population divergence over larger geographical scales (i.e. across different ocean basins). We suggest that the relationship between environmental variables and population structure may be caused by prey behaviour, which is believed to determine common dolphins' movement patterns and preferred associations with certain oceanographic conditions. Our study highlights the role of oceanography in shaping genetic structure of a highly mobile and widely distributed top marine predator. Thus, seascape genetic studies can potentially track the biological effects of ongoing climate-change at oceanographic interfaces and also inform marine reserve design in relation to the distribution and genetic connectivity of charismatic and ecologically important megafauna

Multi-gene evidence for a new bottlenose dolphin species in southern Australia

8 page(s

Abundance and Potential Biological Removal of Common Dolphins Subject to Fishery Impacts in South Australian Waters

Conservation management of wildlife species should be underpinned by knowledge of their distribution and abundance, as well as impacts of human activities on their populations and habitats. Common dolphins (Delphinus delphis) are subject to incidental capture in a range of Australia’s commercial fisheries including gill netting, purse seining and mid-water trawling. The impact these fishery interactions have on common dolphin populations is uncertain, as estimates of abundance are lacking, particularly for the segments of the populations at risk of bycatch and in greater need of protection. Here we used double-observer platform aerial surveys and mark-recapture distance sampling methods to estimate the abundance of common dolphins in 2011 over an area of 42,438 km$^{2}$ in central South Australia, where incidental mortality of common dolphins due to fisheries bycatch is the highest. We also used the potential biological removal (PBR) method to estimate sustainable levels of human-caused mortality for this segment of the population. The estimated abundance of common dolphins was 21,733 (CV = 0.25; 95% CI = 13,809–34,203) in austral summer/autumn and 26,504 in winter/spring (CV = 0.19; 95% CI = 19,488–36,046). Annual PBR estimates, assuming a conservative maximum population growth rate of R$_{max}$ = 0.02 and a recovery factor of F$_{r}$ = 0.5 for species of unknown conservation status, ranged from 189 (summer/autumn) to 239 dolphins (winter/spring), and from 378 (summer/autumn) to 478 dolphins (winter/spring) with an R$_{max}$ = 0.04. Our results indicate that common dolphins are an abundant dolphin species in waters over the central South Australian continental shelf (up to 100 m deep). Based on the 2011 abundance estimates of this species, the highest estimated bycatch of common dolphins (423 mortalities in 2004/05) in the southern Australian region exceeded the precautionary PBR estimates for this population segment. Recent bycatch levels appear to be below PBR estimates, but low observer coverage and underreporting of dolphin mortalities by fishers means that estimates of dolphin bycatch rates are not robust. The effects of cumulative human impacts on common dolphins are not well understood, and thus we recommend a precautionary management approach to manage common dolphin bycatch based on local abundance estimates

Common dolphins subject to fisheries impacts in Southern Australia are genetically differentiated: implications for conservation

Interactions between short-beaked common dolphins Delphinus delphis and the fishing industry of South Australia (SA) have lead to serious concerns over the long-term viability of the local dolphin population. Common dolphins are gregarious animals with high vagility and are expected to display limited genetic differentiation over large spatial scales. Here, we investigate population genetic structure of southern Australian common dolphins using mitochondrial DNA control region sequences and seven microsatellite markers. We found unexpected levels of genetic differentiation for short-beaked common dolphins over a distance of ~1500 km. Although no genetic structure was observed in common dolphins along the coast of SA, we detected marked differentiation between dolphins from SA and south-eastern Tasmania, suggesting a minimum of two genetic populations in southern Australia. We hypothesize that the ephemeral distribution of small pelagic fish enhances movement and dispersal between dolphin groups at a local level. However, clear differences in water temperature, habitat features and fish abundance between SA and Tasmania may contribute to the contemporary isolation observed between dolphin populations. Our findings have important consequences for developing conservation management strategies, because SA has the largest purse-seine fishery by weight in Australia, and substantial numbers of fatal common dolphin interactions have occurred. In 2004/2005 alone, an estimated 1728 common dolphins were encircled and 377 died over a 7-month period. If these impacts lead to a reduction in population size, it is unlikely that dolphins from the adjacent south-eastern Tasmanian population will replace the lost individuals. Recommendations for assessing the impacts of the fishery are presented. The information herein may also have implications for fisheries-marine mammal interactions in coastal and neritic habitats in other areas of the world. Moreover, we demonstrate that a species commonly thought to be wide ranging can show an unexpected degree of genetic differentiation.11 page(s

Reply to 'Clarifying the interpretation of Hamer et al. (2008) by Bilgmann et al. (2008)'

2 page(s