Update references to preprints

Author: katamartin

articles/forest-offsets-explainer/faq.md

@@ -22,7 +22,7 @@ components:
 
 <Box sx={{ color: 'secondary', '& p': { fontSize: [2, 2, 2, 3] }, '& a': { color: 'secondary', '&:hover': { color: 'primary' }}}}>
 We are publishing responses to frequently asked technical questions about our
-recent article [Systematic over-crediting of forest offsets](/research/forest-offsets-explainer). Most of these questions can be answered by reading our [preprint](https://www.biorxiv.org/content/10.1101/2021.04.28.441870v1.article-info), including the extended methods. To make this information more accessible,
+recent article [Systematic over-crediting of forest offsets](/research/forest-offsets-explainer). Most of these questions can be answered by reading the [paper](https://doi.org/10.1111/gcb.15943), including the extended methods. To make this information more accessible,
 we developed this FAQ.
 
 Prepared by {authors.map((name, i) => i === authors.length - 1 ? `and ${name}` : name).join(', ')}.

articles/forest-offsets-explainer/index.md

@@ -56,7 +56,7 @@ To better understand whether these climate claims hold up in practice, we perfor
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 </Figure>
 
-This article provides an overview of how we identified crediting errors in California's offsets program. For a deeper dive on our methods and analysis, you can read [our preprint](https://doi.org/10.1101/2021.04.28.441870). To better understand its implications, you can read [a story](https://www.propublica.org/article/the-climate-solution-actually-adding-millions-of-tons-of-co2-into-the-atmosphere) by Lisa Song (ProPublica) and James Temple (MIT Technology Review) that covers and contextualizes our findings. Finally, you can browse [an interactive online map](https://carbonplan.org/research/forest-offsets-crediting) of the projects we analyzed, or download the open source [data](https://doi.org/10.5281/zenodo.4630712) and [code](https://github.com/carbonplan/forest-offsets) that underlies our analysis.
+This article provides an overview of how we identified crediting errors in California's offsets program. For a deeper dive on our methods and analysis, you can read [the paper](https://doi.org/10.1111/gcb.15943). To better understand its implications, you can read [a story](https://www.propublica.org/article/the-climate-solution-actually-adding-millions-of-tons-of-co2-into-the-atmosphere) by Lisa Song (ProPublica) and James Temple (MIT Technology Review) that covers and contextualizes our findings. Finally, you can browse [an interactive online map](https://carbonplan.org/research/forest-offsets-crediting) of the projects we analyzed, or download the open source [data](https://doi.org/10.5281/zenodo.4630712) and [code](https://github.com/carbonplan/forest-offsets) that underlies our analysis.
 
 ## Background
 
@@ -121,7 +121,7 @@ To quantify these errors systematically, we replaced projects’ common practice
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-Our analysis relied on the [digitized project records](https://doi.org/10.5281/zenodo.4630684) described above, as well as public data from the US Forest Service [Forest Inventory Analysis](https://www.fia.fs.fed.us/) program and the open source [rFIA package](https://github.com/hunter-stanke/rFIA). Our methods are described in detail in [our preprint](https://doi.org/10.1101/2021.04.28.441870) and all of the [code](https://github.com/carbonplan/forest-offsets) and [additional data](https://doi.org/10.5281/zenodo.4630712) underlying our analysis is open source and fully reproducible.
+Our analysis relied on the [digitized project records](https://doi.org/10.5281/zenodo.4630684) described above, as well as public data from the US Forest Service [Forest Inventory Analysis](https://www.fia.fs.fed.us/) program and the open source [rFIA package](https://github.com/hunter-stanke/rFIA). Our methods are described in detail in [the paper](https://doi.org/10.1111/gcb.15943) and all of the [code](https://github.com/carbonplan/forest-offsets) and [additional data](https://doi.org/10.5281/zenodo.4630712) underlying our analysis is open source and fully reproducible.
 
 Across the program as a whole, we estimate net over-crediting of 30 million tCO₂e total (90% CI: 20.5 to 38.6 million tCO₂e) or 29.4% of the credits we analyzed (90% CI: 20.1 to 37.8%). At recent market prices of $13.67 per offset credit,<Cite id='market.transfers'/> these excess credits are worth $410 million (90% CI: $280 to $528 million) — and likely more, as market prices would rise if market regulators took steps to correct for over-crediting.
 

articles/forest-risks-explainer/index.md

@@ -16,7 +16,7 @@ color: red
 quickLook: A detailed look at the disturbance risks to forest carbon under future climate conditions
 background: articles/009/forest-fire-red
 card: forest-risks-explainer
-summary: Forests in the United States are already at risk from wildfire, drought, and insects, and climate change is making it worse. We combined satellite and ecological data with climate models to project future risks to forest carbon. Along with a preprint, we are releasing open data, open software, and an interactive web map.
+summary: Forests in the United States are already at risk from wildfire, drought, and insects, and climate change is making it worse. We combined satellite and ecological data with climate models to project future risks to forest carbon. Along with the paper, we are releasing open data, open software, and an interactive web map.
 version: 1.0.0
 icon: articles/009/forest-fire-small-red
 links:

articles/seaweed-farming-explainer/index.md

@@ -47,7 +47,7 @@ In the case of seaweed carbon removal, the carbon removed by sinking seaweed doe
 
 Similarly, potential avoided emissions from seaweed will depend on the type and source of agricultural products being displaced. For example, growing soybeans releases considerable quantities of non-CO₂ GHGs on average; using farmed seaweed to displace soy protein in animal feed could avoid 0.7 tons of CO₂e GHGs per ton of dry seaweed that would have otherwise been emitted by producing soybeans.<Cite id='hong.2021' /> The size of the market for seaweed-derived products will further depend on demand and reliable market values for such seaweed-based products.
 
-The productivity, costs, and potential climate benefits of seaweed farming are spatially heterogeneous and scale-dependent, and it is important to evaluate the key sensitivities and trade-offs relevant to investors and decision-makers. We have developed coupled biophysical and technoeconomic models to begin answering these questions. Here we explain those models and the interactive tool we built to make them more accessible. We also discuss key insights and priorities for future research. For a deeper dive into our technoeconomic model and analysis, you can try the [map explorer tool](https://carbonplan.org/research/seaweed-farming) or read our [preprint](https://doi.org/10.31223/X5PG9V).
+The productivity, costs, and potential climate benefits of seaweed farming are spatially heterogeneous and scale-dependent, and it is important to evaluate the key sensitivities and trade-offs relevant to investors and decision-makers. We have developed coupled biophysical and technoeconomic models to begin answering these questions. Here we explain those models and the interactive tool we built to make them more accessible. We also discuss key insights and priorities for future research. For a deeper dive into our technoeconomic model and analysis, you can try the [map explorer tool](https://carbonplan.org/research/seaweed-farming) or read the [paper](https://doi.org/10.1038/s41477-022-01305-9).
 
 ## Technoeconomic model