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@@ -81,7 +81,7 @@ @inproceedings{dabbish_social_2012
 @article{elfes_regional-scale_2014,
 	title = {A Regional-Scale Ocean Health Index for Brazil},
 	volume = {9},
-	url = {http://dx.doi.org/10.1371/journal.pone.0092589},
+	url = {https://doi.org/10.1371/journal.pone.0092589},
 	doi = {10.1371/journal.pone.0092589},
 	abstract = {Brazil has one of the largest and fastest growing economies and one of the largest coastlines in the world, making human use and enjoyment of coastal and marine resources of fundamental importance to the country. Integrated assessments of ocean health are needed to understand the condition of a range of benefits that humans derive from marine systems and to evaluate where attention should be focused to improve the health of these systems. Here we describe the first such assessment for Brazil at both national and state levels. We applied the Ocean Health Index framework, which evaluates ten public goals for healthy oceans. Despite refinements of input data and model formulations, the national score of 60 (out of 100) was highly congruent with the previous global assessment for Brazil of 62. Variability in scores among coastal states was most striking for goals related to mariculture, protected areas, tourism, and clean waters. Extractive goals, including Food Provision, received low scores relative to habitat-related goals, such as Biodiversity. This study demonstrates the applicability of the Ocean Health Index at a regional scale, and its usefulness in highlighting existing data and knowledge gaps and identifying key policy and management recommendations. To improve Brazil's ocean health, this study suggests that future actions should focus on: enhancing fisheries management, expanding marine protected areas, and monitoring coastal habitats.},
 	pages = {e92589},
@@ -130,7 +130,7 @@ @article{halpern_elicited_2013
 @article{halpern_assessing_2014,
 	title = {Assessing the Health of the U.S. West Coast with a Regional-Scale Application of the Ocean Health Index},
 	volume = {9},
-	url = {http://dx.doi.org/10.1371/journal.pone.0098995},
+	url = {https://doi.org/10.1371/journal.pone.0098995},
 	doi = {10.1371/journal.pone.0098995},
 	abstract = {Management of marine ecosystems increasingly demands comprehensive and quantitative assessments of ocean health, but lacks a tool to do so. We applied the recently developed Ocean Health Index to assess ocean health in the relatively data-rich {US} west coast region. The overall region scored 71 out of 100, with sub-regions scoring from 65 (Washington) to 74 (Oregon). Highest scoring goals included tourism and recreation (99) and clean waters (87), while the lowest scoring goals were sense of place (48) and artisanal fishing opportunities (57). Surprisingly, even in this well-studied area data limitations precluded robust assessments of past trends in overall ocean health. Nonetheless, retrospective calculation of current status showed that many goals have declined, by up to 20\%. In contrast, near-term future scores were on average 6\% greater than current status across all goals and sub-regions. Application of hypothetical but realistic management scenarios illustrate how the Index can be used to predict and understand the tradeoffs among goals and consequences for overall ocean health. We illustrate and discuss how this index can be used to vet underlying assumptions and decisions with local stakeholders and decision-makers so that scores reflect regional knowledge, priorities and values. We also highlight the importance of ongoing and future monitoring that will provide robust data relevant to ocean health assessment.},
 	pages = {e98995},
@@ -331,7 +331,7 @@ @article{ram_git_2013
 	title = {Git can facilitate greater reproducibility and increased transparency in science},
 	volume = {8},
 	issn = {1751-0473},
-	url = {http://dx.doi.org/10.1186/1751-0473-8-7},
+	url = {https://doi.org/10.1186/1751-0473-8-7},
 	doi = {10.1186/1751-0473-8-7},
 	abstract = {Reproducibility is the hallmark of good science. Maintaining a high degree of transparency in scientific reporting is essential not just for gaining trust and credibility within the scientific community but also for facilitating the development of new ideas. Sharing data and computer code associated with publications is becoming increasingly common, motivated partly in response to data deposition requirements from journals and mandates from funders. Despite this increase in transparency, it is still difficult to reproduce or build upon the findings of most scientific publications without access to a more complete workflow.},
 	pages = {7},
@@ -923,7 +923,7 @@ @article{kervin_common_2013
 @article{halpern_patterns_2015,
 	title = {Patterns and emerging trends in global ocean health},
 	volume = {10},
-	url = {http://dx.doi.org/10.1371/journal.pone.0117863},
+	url = {https://doi.org/10.1371/journal.pone.0117863},
 	doi = {10.1371/journal.pone.0117863},
 	abstract = {International and regional policies aimed at managing ocean ecosystem health need quantitative and comprehensive indices to synthesize information from a variety of sources, consistently measure progress, and communicate with key constituencies and the public. Here we present the second annual global assessment of the Ocean Health Index, reporting current scores and annual changes since 2012, recalculated using updated methods and data based on the best available science, for 221 coastal countries and territories. The Index measures performance of ten societal goals for healthy oceans on a quantitative scale of increasing health from 0 to 100, and combines these scores into a single Index score, for each country and globally. The global Index score improved one point (from 67 to 68), while many country-level Index and goal scores had larger changes. Per-country Index scores ranged from 41–95 and, on average, improved by 0.06 points (range -8 to +12). Globally, average scores increased for individual goals by as much as 6.5 points (coastal economies) and decreased by as much as 1.2 points (natural products). Annual updates of the Index, even when not all input data have been updated, provide valuable information to scientists, policy makers, and resource managers because patterns and trends can emerge from the data that have been updated. Changes of even a few points indicate potential successes (when scores increase) that merit recognition, or concerns (when scores decrease) that may require mitigative action, with changes of more than 10–20 points representing large shifts that deserve greater attention. Goal scores showed remarkably little covariance across regions, indicating low redundancy in the Index, such that each goal delivers information about a different facet of ocean health. Together these scores provide a snapshot of global ocean health and suggest where countries have made progress and where a need for further improvement exists.},
 	pages = {e0117863},
@@ -1200,7 +1200,7 @@ @online{open_science_collaboration_reproducibility_2016
 @article{frew_environmental_2012,
 	title = {Environmental Informatics},
 	volume = {37},
-	url = {http://dx.doi.org/10.1146/annurev-environ-042711-121244},
+	url = {https://doi.org/10.1146/annurev-environ-042711-121244},
 	doi = {10.1146/annurev-environ-042711-121244},
 	abstract = {Environmental informatics uses large multidimensional, complex datasets to study environmental problems, which can be both discrete and continuous in space or time. These datasets and their requisite metadata can be managed by queryable databases. Geospatial Web application programming interfaces ({APIs}) provide remote access to dynamic subsets of environmental information. Persistent identifiers make data citable. The storage-computing trade-off is now heavily skewed in favor of moving calculations to the data. Provenance metadata help determine a data object's reliability and trustworthiness. Rising atmospheric {CO}2, the Antarctic ozone hole, and Gulf Stream warm-core rings were all discovered by analyzing long-term datasets. Similar work continues on mapping evapotranspiration and snow water equivalent. In these “fourth paradigm” problems, data (especially data collected operationally) drive hypothesis formation. Making data available requires new discovery mechanisms and policies favoring data sharing. Cloud computing and array-friendly databases will help bring processing to the data. Ubiquitous location sensing and geotagging will help turn citizen scientists into environmental information collectors.},
 	pages = {449--472},
@@ -1355,7 +1355,7 @@ @article{wickham_layered_2010
 	title = {A Layered Grammar of Graphics},
 	volume = {19},
 	issn = {1061-8600},
-	url = {http://dx.doi.org/10.1198/jcgs.2009.07098},
+	url = {https://doi.org/10.1198/jcgs.2009.07098},
 	doi = {10.1198/jcgs.2009.07098},
 	abstract = {A grammar of graphics is a tool that enables us to concisely describe the components of a graphic. Such a grammar allows us to move beyond named graphics (e.g., the “scatterplot”) and gain insight into the deep structure that underlies statistical graphics. This article builds on Wilkinson, Anand, and Grossman (2005), describing extensions and refinements developed while building an open source implementation of the grammar of graphics for R, ggplot2. The topics in this article include an introduction to the grammar by working through the process of creating a plot, and discussing the components that we need. The grammar is then presented formally and compared to Wilkinson’s grammar, highlighting the hierarchy of defaults, and the implications of embedding a graphical grammar into a programming language. The power of the grammar is illustrated with a selection of examples that explore different components and their interactions, in more detail. The article concludes by discussing some perceptual issues, and thinking about how we can build on the grammar to learn how to create graphical “poems.” Supplemental materials are available online.},
 	pages = {3--28},
@@ -1703,4 +1703,4 @@ @article{becker_enhancing_2015
 	keywords = {Statistics - Computation},
 	annotation = {Comment: Submitted to the Journal of Statistical Software},
 	file = {arXiv.org Snapshot:/Users/julialowndes/Library/Application Support/Zotero/Profiles/8h507e5k.default/zotero/storage/GSSXA638/1501.html:text/html;Becker et al - 2015 - Enhancing reproducibility and collaboration via management of R package cohorts.pdf:/Users/julialowndes/Library/Application Support/Zotero/Profiles/8h507e5k.default/zotero/storage/FQM2GDCI/Becker et al - 2015 - Enhancing reproducibility and collaboration via management of R package cohorts.pdf:application/pdf}
-}
+}