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1.
Sci Rep ; 13(1): 2525, 2023 02 13.
Article in English | MEDLINE | ID: mdl-36782007

ABSTRACT

While population declines among Adélie penguins and population increases among gentoo penguins on the Western Antarctic Peninsula are well established, the logistical challenges of operating in the sea ice-heavy northern tip of the Antarctic Peninsula have prohibited reliable monitoring of seabirds in this region. Here we describe the findings of an expedition to the northern and eastern sides of the Antarctic Peninsula-a region at the nexus of two proposed Marine Protected Areas-to investigate the distribution and abundance of penguins in this region. We discovered several previously undocumented penguin colonies, completed direct surveys of three colonies initially discovered in satellite imagery, and re-surveyed several colonies last surveyed more than a decade ago. Whereas our expectation had been that the Peninsula itself would divide the areas undergoing ecological transition and the apparently more stable Weddell Sea region, our findings suggest that the actual transition zone lies in the so-called "Adélie gap," a 400-km stretch of coastline in which Adélies are notably absent. Our findings suggest that the region north and east of this gap represents a distinct ecoregion whose dynamics stand in sharp contrast to surrounding areas and is likely to be impacted by future conservation measures.


Subject(s)
Spheniscidae , Animals , Antarctic Regions , Population Dynamics , Ice Cover , Satellite Imagery
2.
Sensors (Basel) ; 21(3)2021 Feb 01.
Article in English | MEDLINE | ID: mdl-33535463

ABSTRACT

The emergence of very high-resolution (VHR) satellite imagery (less than 1 m spatial resolution) is creating new opportunities within the fields of ecology and conservation biology. The advancement of sub-meter resolution imagery has provided greater confidence in the detection and identification of features on the ground, broadening the realm of possible research questions. To date, VHR imagery studies have largely focused on terrestrial environments; however, there has been incremental progress in the last two decades for using this technology to detect cetaceans. With advances in computational power and sensor resolution, the feasibility of broad-scale VHR ocean surveys using VHR satellite imagery with automated detection and classification processes has increased. Initial attempts at automated surveys are showing promising results, but further development is necessary to ensure reliability. Here we discuss the future directions in which VHR satellite imagery might be used to address urgent questions in whale conservation. We highlight the current challenges to automated detection and to extending the use of this technology to all oceans and various whale species. To achieve basin-scale marine surveys, currently not feasible with any traditional surveying methods (including boat-based and aerial surveys), future research requires a collaborative effort between biology, computation science, and engineering to overcome the present challenges to this platform's use.


Subject(s)
Satellite Imagery , Whales , Animals , Reproducibility of Results
3.
Sci Rep ; 10(1): 19474, 2020 11 10.
Article in English | MEDLINE | ID: mdl-33173126

ABSTRACT

Using satellite imagery, drone imagery, and ground counts, we have assembled the first comprehensive global population assessment of Chinstrap penguins (Pygoscelis antarctica) at 3.42 (95th-percentile CI: [2.98, 4.00]) million breeding pairs across 375 extant colonies. Twenty-three previously known Chinstrap penguin colonies are found to be absent or extirpated. We identify five new colonies, and 21 additional colonies previously unreported and likely missed by previous surveys. Limited or imprecise historical data prohibit our assessment of population change at 35% of all Chinstrap penguin colonies. Of colonies for which a comparison can be made to historical counts in the 1980s, 45% have probably or certainly declined and 18% have probably or certainly increased. Several large colonies in the South Sandwich Islands, where conditions apparently remain favorable for Chinstrap penguins, cannot be assessed against a historical benchmark. Our population assessment provides a detailed baseline for quantifying future changes in Chinstrap penguin abundance, sheds new light on the environmental drivers of Chinstrap penguin population dynamics in Antarctica, and contributes to ongoing monitoring and conservation efforts at a time of climate change and concerns over declining krill abundance in the Southern Ocean.


Subject(s)
Conservation of Natural Resources/methods , Feeding Behavior/physiology , Satellite Imagery/methods , Spheniscidae/physiology , Animal Distribution , Animals , Antarctic Regions , Climate Change , Euphausiacea/physiology , Geography , Islands , Population Density , Population Dynamics , Seasons , Spheniscidae/classification
4.
PLoS One ; 14(10): e0212532, 2019.
Article in English | MEDLINE | ID: mdl-31574136

ABSTRACT

Most cetacean species are wide-ranging and highly mobile, creating significant challenges for researchers by limiting the scope of data that can be collected and leaving large areas un-surveyed. Aerial surveys have proven an effective way to locate and study cetacean movements but are costly and limited in spatial extent. Here we present a semi-automated pipeline for whale detection from very high-resolution (sub-meter) satellite imagery that makes use of a convolutional neural network (CNN). We trained ResNet, and DenseNet CNNs using down-scaled aerial imagery and tested each model on 31 cm-resolution imagery obtained from the WorldView-3 sensor. Satellite imagery was tiled and the trained algorithms were used to classify whether or not a tile was likely to contain a whale. Our best model correctly classified 100% of tiles with whales, and 94% of tiles containing only water. All model architectures performed well, with learning rate controlling performance more than architecture. While the resolution of commercially-available satellite imagery continues to make whale identification a challenging problem, our approach provides the means to efficiently eliminate areas without whales and, in doing so, greatly accelerates ocean surveys for large cetaceans.


Subject(s)
Cetacea/physiology , Deep Learning , Satellite Imagery , Animals
5.
Sci Rep ; 8(1): 3926, 2018 03 02.
Article in English | MEDLINE | ID: mdl-29500389

ABSTRACT

Despite concerted international effort to track and interpret shifts in the abundance and distribution of Adélie penguins, large populations continue to be identified. Here we report on a major hotspot of Adélie penguin abundance identified in the Danger Islands off the northern tip of the Antarctic Peninsula (AP). We present the first complete census of Pygoscelis spp. penguins in the Danger Islands, estimated from a multi-modal survey consisting of direct ground counts and computer-automated counts of unmanned aerial vehicle (UAV) imagery. Our survey reveals that the Danger Islands host 751,527 pairs of Adélie penguins, more than the rest of AP region combined, and include the third and fourth largest Adélie penguin colonies in the world. Our results validate the use of Landsat medium-resolution satellite imagery for the detection of new or unknown penguin colonies and highlight the utility of combining satellite imagery with ground and UAV surveys. The Danger Islands appear to have avoided recent declines documented on the Western AP and, because they are large and likely to remain an important hotspot for avian abundance under projected climate change, deserve special consideration in the negotiation and design of Marine Protected Areas in the region.


Subject(s)
Animal Distribution , Geographic Mapping , Satellite Imagery/methods , Spheniscidae/growth & development , Animals , Climate Change , Islands , Population Dynamics , Spheniscidae/physiology
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