- Dryad submission
- xml parsing example to Scott
- essentially see (fishbase example , and xpath tutoral )
- knitr and latex figure placement (use float package with H to enforce placement).
- cc0 & OSI …
- pmc purchase order, dryad data id approval.
- & writing writing writing…
- Re-formating data for ggplot version of graphs, realized I should be specifying id.vars to melt (example from my Q on SO)
- Great special feature on the data era in TREE ((which I mention despite it’s misfortune of being connected to Elsivier right now)) (Page, 2012), (Michener & Jones, 2012), (Porter et. al. 2012), (Hochachka et. al. 2012), (Parr et. al. 2012), (Brewer et. al. 2012).
- Digital lab notebooks in Nature (again) (Giles, 2012).
- Nice ecosphere paper on warning signals Bestelmeyer et. al. 2011
Four conclusions, not surprising perhaps but nice message:
- The utility of leading indicators is often limited and can depend on the abruptness,
- information on spatiotemporal context is useful
- and ancillary information from associated experiments and observations aids interpretation
- underscores the utility of long-term observations
Applying 5 approaches to each candidate set of data for transitions
- “visualizing patterns” i.e. loess smoothed curves
- Unimodality in frequency.
- rising variance
- “predictor-response” i.e. regressions
(2 and 5 are confounded by switching between two stable states that have equal stability/spring constants. I think they’d do better to test for unimodality in time than in frequency when analyzing across break-points.) Notably the code though not the data is posted on the Ecological archive.
They find 3 data sets have true transitions with hysteresis, 1 which appears to simply linearly track a changing environment.
- Hehe, I get acknowledged in a PNAS astrophysics article (Spiegel & Turner, 2011)
- Simple mechanistic models outperforming big autoregressive moving average models.
Page R (2012). “Space, Time, Form: Viewing The Tree of Life.” Trends in Ecology & Evolution, 27. ISSN 01695347, https://dx.doi.org/10.1016/j.tree.2011.12.002.
Michener W and Jones M (2012). “Ecoinformatics: Supporting Ecology as A Data-Intensive Science.” Trends in Ecology & Evolution, 27. ISSN 01695347, https://dx.doi.org/10.1016/j.tree.2011.11.016.
Porter J, Hanson P and Lin C (2012). “Staying Afloat in The Sensor Data Deluge.” Trends in Ecology & Evolution, 27. ISSN 01695347, https://dx.doi.org/10.1016/j.tree.2011.11.009.
Hochachka W, Fink D, Hutchinson R, Sheldon D, Wong W and Kelling S (2012). “Data-Intensive Science Applied to Broad-Scale Citizen Science.” Trends in Ecology & Evolution, 27. ISSN 01695347, https://dx.doi.org/10.1016/j.tree.2011.11.006.
Parr C, Guralnick R, Cellinese N and Page R (2012). “Evolutionary Informatics: Unifying Knowledge About The Diversity of Life.” Trends in Ecology & Evolution, 27. ISSN 01695347, https://dx.doi.org/10.1016/j.tree.2011.11.001.
Brewer S, Jackson S and Williams J (2012). “Paleoecoinformatics: Applying Geohistorical Data to Ecological Questions.” Trends in Ecology & Evolution, 27. ISSN 01695347, https://dx.doi.org/10.1016/j.tree.2011.09.009.
Giles J (2012). “Going Paperless: The Digital Lab.” Nature, 481. ISSN 0028-0836, https://dx.doi.org/10.1038/481430a.
Spiegel D and Turner E (2011). “Bayesian Analysis of The Astrobiological Implications of Life’S Early Emergence on Earth.” Proceedings of The National Academy of Sciences, 109. ISSN 0027-8424, https://dx.doi.org/10.1073/pnas.1111694108.
Analysis of Abrupt Transitions in Ecological Systems, Brandon T. Bestelmeyer, Aaron M. Ellison, William R. Fraser, Kristen B. Gorman, Sally J. Holbrook, Christine M. Laney, Mark D. Ohman, Debra P. C. Peters, Finn C. Pillsbury, Andrew Rassweiler, Russell J. Schmitt, Sapna Sharma, (2011) Ecosphere, 2 10.1890/ES11-00216.1