K. Ono

Global and Planetary Change · with Hordyk · 2015–2016

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Global and Planetary Change — 37 citations into it; #4,264 of 10,225 by trust here, #5,517 by citations
• Nature and Landscape Conservation — 28 citations into it; #2,958 of 6,941 by trust here, #4,071 by citations
• Aquatic Science — 11 citations into it; #354 of 1,160 by trust here, #664 by citations
• Ecology — 10 citations into it

Whom K. Ono trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Adrian R. Hordyk
2. J. Prince
3. Ray Hilborn
4. Carl J Walters
5. N. Loneragan
6. S. Valencia
7. Arni Magnusson
8. P. Pepin
9. André E. Punt
10. K. Sainsbury

Who trusts K. Ono overall

1. Adrian R. Hordyk
2. J. Prince
3. N. Loneragan
4. T. Mildenberger

Papers from K. Ono's perspective

Ordered by how strongly the researchers K. Ono trusts endorse each paper. Same corpus, a different order for every researcher.

1. Quantitative fisheries stock assessment: Choice, dynamics and uncertainty (Reviews in Fish Biology and Fisheries)
2. AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models (Optim. Methods Softw.)
3. Fisheries Ecology and Management
4. A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor fisheries
5. Evolutionary assembly rules for fish life histories
6. Stock and recruitment: generalizations about maximum reproductive rate, density dependence, and variability using meta-analytic approaches
7. A Review of the Lifespans and Mortality Rates of Fish in Nature, and Their Relation to Growth and Other Physiological Characteristics
8. Reflections on the success of traditional fisheries management
9. F35% Revisited Ten Years Later
10. Analytical reference points for age-structured models: application to data-poor fisheries

Their papers

• A simple length-structured model based on life history ratios and incorporating size-dependent selectivity: application to spawning potential ratios for data-poor stocks (2016) — 111 citations
• A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor fisheries (2015) — 396 citations
• Some explorations of the life history ratios to describe length composition, spawning-per-recruit, and the spawning potential ratio (2015) — 221 citations