Abstract:Remote, high-latitude oceans can prove challenging for the designation and implementation of marine protected areas (MPAs), partly due to issues in monitoring inaccessible localities and large spatial scales. A lack of protection combined with damage from growing human activities has contributed to the degradation of some of the Earth's richest marine biodiversity and highlights the urgent need to support improved marine conservation. High-resolution satellite imagery (VHR; 0.3-0.6 m spatial resolution) provid… Show more
“…Across all eight regions, trends in fast ice extent were only weakly correlated with the probability of population declines (figure 3; Spearman rank correlation = −0.52), suggesting that other factors must be at play. Figure 2Regional dynamics of emperor penguin populations (indices of abundance of adult penguins observed from VHR imagery during each austral spring on the Y -axis, which is fixed from 0 at the origin to a maximum of 100 000 birds; colony codes defined in [5]), defined by fast ice region [28] during the study period (2009–2018). For inset charts, the central lines represent the median of the posterior distributions, while outer bands represent 95% equal-tailed CIs for the annual indices.Figure 3Relationship between probability of regional population decline of emperor penguins (indices of abundance of adult birds present in springtime at colonies during 2009–2018) and 18-year trend in regional fast ice extent (from table 1 in [28]).…”
Section: Resultsmentioning
confidence: 99%
“…Across all eight regions, trends in fast ice extent were only weakly correlated with the probability of population declines ( figure 3 ; Spearman rank correlation = −0.52), suggesting that other factors must be at play. Figure 2 Regional dynamics of emperor penguin populations (indices of abundance of adult penguins observed from VHR imagery during each austral spring on the Y -axis, which is fixed from 0 at the origin to a maximum of 100 000 birds; colony codes defined in [ 5 ]), defined by fast ice region [ 28 ] during the study period (2009–2018). For inset charts, the central lines represent the median of the posterior distributions, while outer bands represent 95% equal-tailed CIs for the annual indices.…”
Section: Resultsmentioning
confidence: 99%
“…In contrast, counts, but not demographic analysis, at Cape Crozier in the Ross Sea over a period of approximately 60 years indicate colony size fluctuations [ 3 , 4 ]. Effective understanding of colony dynamics, thus, requires a regional perspective [ 5 ]. Recently, with the development of high-resolution satellite imagery (VHR; 30–60 cm spatial resolution), detecting and quantifying populations of many animal species (e.g.…”
Like many polar animals, emperor penguin populations are challenging to monitor because of the species' life history and remoteness. Consequently, it has been difficult to establish its global status, a subject important to resolve as polar environments change. To advance our understanding of emperor penguins, we combined remote sensing, validation surveys and using Bayesian modelling, we estimated a comprehensive population trajectory over a recent 10-year period, encompassing the entirety of the species’ range. Reported as indices of abundance, our study indicates with 81% probability that there were fewer adult emperor penguins in 2018 than in 2009, with a posterior median decrease of 9.6% (95% credible interval (CI) −26.4% to +9.4%). The global population trend was −1.3% per year over this period (95% CI = −3.3% to +1.0%) and declines probably occurred in four of eight fast ice regions, irrespective of habitat conditions. Thus far, explanations have yet to be identified regarding trends, especially as we observed an apparent population uptick toward the end of time series. Our work potentially establishes a framework for monitoring other Antarctic coastal species detectable by satellite, while promoting a need for research to better understand factors driving biotic changes in the Southern Ocean ecosystem.
“…Across all eight regions, trends in fast ice extent were only weakly correlated with the probability of population declines (figure 3; Spearman rank correlation = −0.52), suggesting that other factors must be at play. Figure 2Regional dynamics of emperor penguin populations (indices of abundance of adult penguins observed from VHR imagery during each austral spring on the Y -axis, which is fixed from 0 at the origin to a maximum of 100 000 birds; colony codes defined in [5]), defined by fast ice region [28] during the study period (2009–2018). For inset charts, the central lines represent the median of the posterior distributions, while outer bands represent 95% equal-tailed CIs for the annual indices.Figure 3Relationship between probability of regional population decline of emperor penguins (indices of abundance of adult birds present in springtime at colonies during 2009–2018) and 18-year trend in regional fast ice extent (from table 1 in [28]).…”
Section: Resultsmentioning
confidence: 99%
“…Across all eight regions, trends in fast ice extent were only weakly correlated with the probability of population declines ( figure 3 ; Spearman rank correlation = −0.52), suggesting that other factors must be at play. Figure 2 Regional dynamics of emperor penguin populations (indices of abundance of adult penguins observed from VHR imagery during each austral spring on the Y -axis, which is fixed from 0 at the origin to a maximum of 100 000 birds; colony codes defined in [ 5 ]), defined by fast ice region [ 28 ] during the study period (2009–2018). For inset charts, the central lines represent the median of the posterior distributions, while outer bands represent 95% equal-tailed CIs for the annual indices.…”
Section: Resultsmentioning
confidence: 99%
“…In contrast, counts, but not demographic analysis, at Cape Crozier in the Ross Sea over a period of approximately 60 years indicate colony size fluctuations [ 3 , 4 ]. Effective understanding of colony dynamics, thus, requires a regional perspective [ 5 ]. Recently, with the development of high-resolution satellite imagery (VHR; 30–60 cm spatial resolution), detecting and quantifying populations of many animal species (e.g.…”
Like many polar animals, emperor penguin populations are challenging to monitor because of the species' life history and remoteness. Consequently, it has been difficult to establish its global status, a subject important to resolve as polar environments change. To advance our understanding of emperor penguins, we combined remote sensing, validation surveys and using Bayesian modelling, we estimated a comprehensive population trajectory over a recent 10-year period, encompassing the entirety of the species’ range. Reported as indices of abundance, our study indicates with 81% probability that there were fewer adult emperor penguins in 2018 than in 2009, with a posterior median decrease of 9.6% (95% credible interval (CI) −26.4% to +9.4%). The global population trend was −1.3% per year over this period (95% CI = −3.3% to +1.0%) and declines probably occurred in four of eight fast ice regions, irrespective of habitat conditions. Thus far, explanations have yet to be identified regarding trends, especially as we observed an apparent population uptick toward the end of time series. Our work potentially establishes a framework for monitoring other Antarctic coastal species detectable by satellite, while promoting a need for research to better understand factors driving biotic changes in the Southern Ocean ecosystem.
“…sensing (SRS) and unoccupied aircraft systems (UAS). The campaigns are listed in order of release date, with references (see [40,[146][147][148][149][150][151][152][153][154]) in a separate column. The platform Tomnod has been replaced by GeoHIVE.…”
Section: Recommendations and Future Directionsmentioning
Although many medium-to-large terrestrial vertebrates are still counted by ground or aerial surveys, remote-sensing technologies and image analysis have developed rapidly in recent decades, offering improved accuracy and repeatability, lower costs, speed, expanded spatial coverage and increased potential for public involvement. This review provides an introduction for wildlife biologists and managers relatively new to the field on how to implement remote-sensing techniques (satellite and unoccupied aircraft systems) for counting large vertebrates on land, including marine predators that return to land to breed, haul out or roost, to encourage wider application of these technological solutions. We outline the entire process, including the selection of the most appropriate technology, indicative costs, procedures for image acquisition and processing, observer training and annotation, automation, and citizen science campaigns. The review considers both the potential and the challenges associated with different approaches to remote surveys of vertebrates and outlines promising avenues for future research and method development.
“…The latest advancements of very high-resolution (VHR) optical satellite imagery (below 1 m spatial resolution) show tremendous potential for monitoring wildlife in recent trials [1] , [2] , [3] , [4] , [5] , [6] . There are also a few VHR satellites with synthetic aperture radar (SAR) sensor, which can image in the dark and through clouds by returning an image of the surface roughness.…”
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