21 research outputs found
New approaches to understand species-habitat relationship using Indigenous Knowledge and scientific data
No full textIndigenous Knowledge (IK) holds information on the relationships between animals and their
environment, among many other things. Although the depth of ecological information embodied
within IK is often recognized, it is rarely included in species-habitat models as a sole data source or combined with scientific data. In partnership with IK holders, I have developed methods to include IK in statistical approaches to model species-habitat relationships. First, I documented IK focused on species-habitat relationships of ringed seals (natchiq in Iñupiaq; Pusa hispida), bearded seals (ugruk; Erignathus barbatus), and spotted seals (qasigiaq; Phoca largha), in the waters near three Arctic communities: Utqiaġivk, Tikiġaq, and Kotzebue, Alaska. Results showed that all three species use currents during foraging activity, which is not a behaviour captured by previous satellite telemetry studies, but have differing associations with sea ice and thus potentially different responses to climate change. Regional differences in seal behaviour and habitat between the IK from each community were also apparent, highlighting changes along species migration routes. I then developed methods for species-habitat models that rely on IK as the sole data source. The method provides an approach to interpret different types of IK as probability of species presence associated with different habitat types, including dynamic habitat covariates, and combines them in a single model. I applied the method to ringed seals, providing an approach where IK is presented in a way that can be easily considered and included in current species and ecosystem management frameworks. Next, I developed a method to include IK as informed priors and habitat covariates in Bayesian habitat selection functions applied to animal movement data. I show that the inclusion of IK in habitat selection functions can identify important areas for the species that would not have been predicted using scientific data alone, due to the lack of data at appropriate scales. Overall, my work has provided new methods to include IK in species-habitat modelling, highlighting the depth of ecological information within IK. These methods provide approaches to better our understanding of species-habitat relationships that can fully consider IK in species management and conservation.Graduate and Postdoctoral StudiesGraduat
Objective Evaluation of the Retention of Manual Control Skills Using a Cybernetic Approach
No full textPilots’ manual flying skills have notably reduced due to the increase in flight deck automation over the last decades. This has resulted in a growing concern that today pilots lack the skills to safely and successfully prevent or recover from unexpected aircraft upset events or to take over controls after a sudden transition to manual flying. Although the necessity to reverse this decline in manual flying skills, by developing and implementing additional standards and guidelines for (recurrent) training procedures, is a topic of current interest, additional research is required to be able to implement scientifically substantiated standards to ensure pilots receive sufficient training opportunities to develop, maintain and improve manual flying proficiency. A human-in-the-loop-experiment was conducted to objectively and quantitatively evaluate the acquisition, decay and retention of skill-based manual control behavior in a compensatory dual-axis roll and pitch attitude tracking task. In this study, thirty-eight fully task-naive participants were trained in a fixed-base setting in the Human-Machine Interaction Laboratory at Delft University of Technology and subsequently divided into three groups based on their training performance. Performance of the first group was re-evaluated after a period of non-practice of six months, while the second group was retested at both three and six months after training and skill retention of the third group was measured after two, four and six months. The goal of the experiment was to model the decay curve of skill-based manual control behavior and to determine the reacquisition rate of lost skills compared to their initial acquisition rate. To quantify changes in manual control skills, participants’ control behavior was modeled using quasi-linear human operator models. The results suggest that control skills decay following a negatively accelerating decay curve and that lost skills are reacquired at a higher rate than their initial development rate. However, to construct a decay curve which is able to accurately model skill decay over an extended period of time, a larger-scale experiment should be conducted with a larger number of participants and periods of non-practice ranging from a few hours or days up to several years.Aerospace Engineering | Control & Simulatio
Relationships between accessible prey biomass and sea lion population change in the Aleutian Islands.
No full text<p>The relationships between predicted prey biomass accessible to Steller sea lions (a, b, c) using the reduced prey biomass (Scenario 3) and the annual rate of non-pup population change in the Aleutian Islands were significant for walleye pollock only (a), with western Aleutian rookeries (west, from rookeries 1–8, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123786#pone.0123786.g001" target="_blank">Fig 1</a>) showing a greater change with pollock biomass than eastern Aleutian rookeries (east, from rookeries 9–15, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123786#pone.0123786.g001" target="_blank">Fig 1</a>).</p
Annual biomass of pollock, cod and mackerel caught by fisheries.
No full text<p>Average annual biomass (1000s of tons) of Atka mackerel (a,d), Pacific cod (b,e) and walleye pollock (c,f) commercially caught within 10 and 20 (d, e, f) and 50 and 100 (a, b, c) km of the rookeries from 2000–2004. There has been no directed fishery for mackerel in the Bering Sea and Gulf of Alaska since 1996.</p
Sea lion population change and the biomass of prey accessible to sea lions.
No full text<p>The average numbers of Steller sea lions (age 1+ y), annual rate of sea lion population change and predicted biomass of groundfish accessible (calculated according to our accessibility model) to sea lions at each rookery or rookery cluster (shown with brackets): (a) Average non-pup population change and population size from 2000–2008, (b) average biomass of Atka mackerel accessible, (c) average biomass of Pacific cod accessible; and (d) average biomass of walleye pollock accessible. Biomasses averages are for 2000/2002/2004 in the Aleutian Islands (AI) and 2001/2003 in the Gulf of Alaska (GOA). Mackerel surveys are not conducted in the Bering Sea and Gulf of Alaska as the species’ distribution is limited in those regions.</p
Locations of catches relative to predicted biomass distributions.
No full text<p>Biomass distributions (t/9x9 km<sup>2</sup> grid cell) are shown for (a) walleye pollock available in the Aleutian Islands (2000), Bering Sea (2001) and Gulf of Alaska (2001), (b) Pacific cod available in the Aleutian Islands (2002), Bering Sea (2003) and Gulf of Alaska (2003), and (c) Atka mackerel available in the Aleutian Islands (2004) (modified from S1). Locations of catches (dots) shown are from the same years as the corresponding prey distributions (Aleutian Islands: pale purple, Bering Sea and Gulf of Alaska: dark purple).</p
The locations of the 33 Steller sea lion rookeries studied.
No full text<p>(1) Attu Cape Wrangell (2) Agattu Gillon Point (3) Agattu Cape Sabak (4) Buldir (5) Kiska Cape St Stephen (6) Kiska Lief Cove (7) Ayugadak (8) Amchitka Column Rock (9) Ulak Hasgox Point (10) Tag (11) Gramp Rock (12) Adak Lake Point (13) Kasatochi North Point (14) Seguam Saddle Ridge (15) Yunaska (16) Adugak (17) Ogchul (18) Bogoslof Fire Island (19) Akutan Cape Morgan (20) Akun Billings Head (21) Ugamak Round (22) Sea Lion Rock Amak (23) Clubbing Rocks North (24) Pinnacle Rock (25) Chernabura (26) Atkins (27) Chowiet (28) Chirikof (29) Sugarloaf (30) Marmot (31) Outer Pye (32) Wooded Fish (33) Seal Rocks. Rookeries were grouped into 4 regions (western Aleutian Islands—(1)-(8), eastern Aleutian Islands—(9)-(15), western Gulf of Alaska—(16)-(22), eastern Gulf of Alaska—(23)-(33)).</p
Annual catch in t/9x9 km<sup>2</sup> of (a) walleye pollock (2003), (b) Pacific cod (2002) and (c) Atka mackerel (2004).
No full text<p>Total amounts removed within 10, 20, 50 and 100 km of each rookery (red, cyan, orange and purple rings respectively) were calculated by summing the total biomass of catches within each of the respective rings.</p
Assessment of Competition between Fisheries and Steller Sea Lions in Alaska Based on Estimated Prey Biomass, Fisheries Removals and Predator Foraging Behaviour.
No full textA leading hypothesis to explain the dramatic decline of Steller sea lions (Eumetopias jubatus) in western Alaska during the latter part of the 20th century is a change in prey availability due to commercial fisheries. We tested this hypothesis by exploring the relationships between sea lion population trends, fishery catches, and the prey biomass accessible to sea lions around 33 rookeries between 2000 and 2008. We focused on three commercially important species that have dominated the sea lion diet during the population decline: walleye pollock, Pacific cod and Atka mackerel. We estimated available prey biomass by removing fishery catches from predicted prey biomass distributions in the Aleutian Islands, Bering Sea and Gulf of Alaska; and modelled the likelihood of sea lions foraging at different distances from rookeries (accessibility) using satellite telemetry locations of tracked animals. We combined this accessibility model with the prey distributions to estimate the prey biomass accessible to sea lions by rookery. For each rookery, we compared sea lion population change to accessible prey biomass. Of 304 comparisons, we found 3 statistically significant relationships, all suggesting that sea lion populations increased with increasing prey accessibility. Given that the majority of comparisons showed no significant effect, it seems unlikely that the availability of pollock, cod or Atka mackerel was limiting sea lion populations in the 2000s
Relationships between accessible prey biomass and sea lion population change in the Gulf of Alaska.
No full text<p>The relationships between predicted prey biomass of walleye pollock (a, c) and Pacific cod (b, d) accessible to sea lions using the reduced (Scenario 1; a, b) and unreduced biomass distributions (c, d), and the annual rate of non-pup population change in the Gulf of Alaska were significantly positive for Pacific cod only. The trends with and without fishery removals accounted for were very similar due to the small amount of cod removed within the accessibility model extents of the rookeries in June and July.</p
