Pygmy blue whale telemetry and biologging data

As is commonly done for many animals where direct observation of foraging is difficult, foraging areas of pygmy blue whales have previously been defined from analysis of data obtained from satellite tracking tags deployed on pygmy blue whales. These studies (Double et al. 2014, Moller et al. 2020 and Thums et al. 2022) documented pygmy blue whale migration between Australia and Indonesia and identified areas where whales spent the most time and where they had movement behaviour (as calculated from surface location estimates from the tags) thought to be indicative of foraging (slower speed and lots of turns), such as the Bonny upwelling region of South Australia, Perth Canyon, NW Cape region and the Banda Sea. Although there is a theoretical basis for assigning putative foraging behaviour along the horizontal movement paths of animals based on such analyses of location estimates from satellite tags (Kareiva & Odell 1987, Zollner & Lima 1999), foraging actually occurs while the animals are diving and so having data from the vertical dimension is important for validation of foraging areas defined using these methods.To characterise and track vertical movement behaviours and validate inferred foraging behaviour from movement models, eight pygmy blue whales were double tagged by AIMS and CWR (in partnership with Woodside) in the Perth Canyon, Western Australia with Fastloc GPS tags (Wildlife Computers LIMPET; Low Impact Minimally Percutaneous Electronic Transmitters, type: SPLASH10-F-333) and pop-up satellite-linked archival tags (PSATs) (Wildlife Computers MiniPAT) in 2021 – 2022, and another double tagged at Ningaloo in 2023. The GPS tags provided location estimates and the PSATs provided depth and summarised accelerometery time-series (Mobility and activity-time series, ATS) data from the whales for up to 40 d duration, encompassing presumed foraging grounds and migration areas. Four PSATs were recovered, providing access to the high-resolution (1 s sample rate of depth and Mobility) data archive on board the tag. For the remaining five tags, the summarised time-series data (75 s sample rate of depth and ATS) transmitted through the Argos satellite network (Argos), was used for the analysis. Given the difficulty of recovering tags from long (> a few days) deployments, both recovered and transmitted datasets were used to determine whether lower temporal resolution depth and accelerometry data transmitted via Argos (compared to the archived data on board recovered tags) can provide sufficient detail to characterise pygmy blue whale diving behaviour, especially foraging and feeding. Diving behaviour was characterised using a supervised Random Forests dive behaviour classification function to determine where and when pygmy blue whales forage. The locations where foraging and lunge feeding dives occurred was compared to areas of putative foraging inferred from a movement model (State-space model) and to important foraging areas previously defined from spatial analyses based on horizontal movement data only (Thums et al. 2022).Transmitted depth time series (75s) was adequate for identifying foraging dives, but accelerometry metrics were key (error increased to 18% without it) to distinguishing lunge feeding dives from foraging dives without lunges.Foraging and lunge feeding dives occurred in three main foraging areas: 1) Centred at the head of the Perth Canyon, extending from offshore of Cape Naturaliste to offshore of Jurien Bay, 2) offshore of Geraldton and the Abrolhos Islands and 3) offshore of Ningaloo, extending from approximately Coral Bay up to offshore of approximately the Montebello Islands (~19 °S). Foraging/ feeding was also detected in the Savu Sea (~8 °S), offshore of Bremer Bay and far off the shelf of the Kimberley region of Western Australia while migrating (~15 °S, ~120 °E).Despite a weak temporal relationship between putative (inferred from a movement model) and actual foraging, there was generally good spatial overlap detected, but predominantly in high use areas with lower use and more opportunistic foraging areas being less likely to be detected by the model. More opportunistic foraging occurred off north-west Australia where foraging dives were shallower, horizontal travel rates faster, and there was an absence of a diurnal pattern in diving. This suggests a reliance on more ephemeral prey than off south-west Australia where whales have high residency.Our test of movement models to define foraging areas is extremely useful given its common usage in ecology and our spatial delineation of foraging areas assists with conservation management.针对诸多难以直接观测觅食行为的动物，学界通常采用卫星追踪标签（satellite tracking tags）数据分析法界定侏儒蓝鲸（pygmy blue whales）的觅食海域。此前已有研究通过部署在侏儒蓝鲸身上的卫星追踪标签获取数据并开展分析，以此划定其觅食区域。 上述研究（Double等人2014年、Moller等人2020年及Thums等人2022年）记录了侏儒蓝鲸在澳大利亚与印度尼西亚之间的洄游路径，并识别出蓝鲸停留时间最长的海域，以及被认为具有觅食特征的移动行为（通过标签的表层位置估算结果计算得出，表现为低移动速度与频繁转向）的海域，例如澳大利亚南部的邦尼上升流区、珀斯峡谷、西北角海域与班达海。 尽管基于卫星标签位置估算结果的此类分析，可为通过动物水平移动路径推定觅食行为提供理论依据（Kareiva & Odell 1987；Zollner & Lima 1999），但觅食行为实际发生于动物潜水过程中，因此获取垂直维度的数据对验证此类方法划定的觅食区域至关重要。 为刻画并追踪垂直移动行为，同时验证基于移动模型推定的觅食行为，研究团队于2021—2022年在西澳大利亚州珀斯峡谷，由澳大利亚海洋科学研究所(AIMS)与野生动物保护组织(CWR)联合伍德赛德公司(Woodside)，为8头侏儒蓝鲸佩戴了双重标签：Fastloc GPS标签（Fastloc GPS tags，Wildlife Computers LIMPET；低影响微创电子发射器，型号：SPLASH10-F-333）与卫星归档弹出式标签（pop-up satellite-linked archival tags, PSATs）（Wildlife Computers MiniPAT）；并于2023年在宁格鲁海域为另一头侏儒蓝鲸佩戴了双重标签。 此类GPS标签可提供位置估算数据，而PSATs则可采集蓝鲸的深度数据与汇总后的加速度计时间序列（运动与活动时间序列，Mobility and activity-time series, ATS），数据采集时长可达40天，覆盖推定的觅食场与洄游区域。 研究共回收4个PSATs，可获取标签内置的高分辨率（深度与运动数据采样率为1秒）归档数据；剩余5个标签则通过Argos卫星网络（Argos）传输了汇总后的时间序列数据（深度与ATS数据采样率为75秒），供后续分析使用。 鉴于长期（超过数天）部署的标签回收难度较大，研究同时使用了回收标签的归档数据与卫星传输数据，以验证通过Argos传输的低时间分辨率深度与加速度计数据（相较于回收标签的内置归档数据），是否足以刻画侏儒蓝鲸的潜水行为，尤其是觅食与摄食行为。 研究采用有监督随机森林（Random Forests）潜水行为分类模型刻画潜水行为，以此确定侏儒蓝鲸的觅食时间与海域。将觅食与冲刺摄食潜水发生的位置，与基于移动模型（状态空间模型，State-space model）推定的觅食区域，以及此前仅基于水平移动数据的空间分析划定的重要觅食区域（Thums等人2022年）进行对比。 75秒采样率的传输深度时间序列数据足以识别觅食潜水，但加速度计指标是区分冲刺摄食潜水与非冲刺觅食潜水的关键（缺失该指标时分类误差升至18%）。 觅食与冲刺摄食潜水主要发生在3个海域：1）以珀斯峡谷头部为中心，覆盖从自然角近海到朱里恩湾近海的区域；2）杰拉尔顿与阿布洛霍斯群岛近海区域；3）宁格鲁近海区域，大致从珊瑚湾延伸至蒙特贝洛群岛近海（南纬约19°）。 研究还在萨武海（南纬约8°）、布雷默湾近海，以及西澳大利亚州金伯利海域远海洄游过程中（南纬约15°、东经约120°）检测到觅食/摄食行为。 尽管基于移动模型推定的觅食行为与实际觅食行为之间的时间相关性较弱，但二者在空间上总体重合度较好，且主要集中在高频使用海域；低频使用与更多机会主义觅食的海域则更难被模型检测到。 澳大利亚西北近海存在更多机会主义觅食行为，该区域的觅食潜水更浅、水平移动速度更快，且潜水行为无昼夜节律。这表明相较于栖息时间较长的西南澳大利亚近海海域，西北近海的蓝鲸依赖更短暂的猎物资源。 鉴于移动模型在生态学研究中应用广泛，本研究对该模型划定觅食区域的验证极具价值；同时，我们对觅食海域的空间划定也可为保护管理工作提供支撑。