Friday, March 1, 2019
As many of you have heard, this is my last day at The Nature Conservancy; I'll be taking a new job at The Pew Charitable Trusts on their conservation science team. I don't know yet what will happen with these summaries but don't despair! I hope to keep them going in some form - likely with a different topical focus. If you know someone who is feeling lucky and wants to sign up to receive these summaries despite the uncertainty, they can do so at http://bit.ly/sciencejon
I've been frantically wrapping up work so have read less science than usual this month. But I did write a blog post explaining why seemingly silly questions like how to define forests and deforestation are actually both tricky and really important: How many trees make a forest? I talk about The Accountability Framework and the critical role it can play in helping to end deforestation:
The only papers I reviewed this month are one about how scientists read scientific literature, and two soil papers (from TNC's Deborah Bossio and Steve Wood) which are both summarized on this blog: https://nature4climate.org/news/headline-stories/time-to-let-soil-shine-a-global-agenda-for-collective-action-on-soil-carbon/
READING SCIENTIFIC LITERATURE:
Colleagues working in applied conservation often tell me they have no time to read scientific literature. Tenopir et al. 2015 is an article about how faculty in five US universities seek out scholarly literature (including but not limited to the sciences)! I'll be honest - I skimmed this looking for two bits of information: scientists reported reading an average of 26 articles per month (Fig 1), and spent 32 minutes on each article (Fig 2). I read fewer articles, and usually read them faster. But even these academics are spending less than two days out of the month on this. Surely most of us can find a few hours! There are some other interesting tidbits here. Almost 2/3 of articles read are from the last two years - so have a good comms plan for your research! Also, NONE of the surveyed scientists read articles on a mobile device like a tablet, which is a huge missed opportunity for those long commutes on mass transit!
Soil organic carbon (SOC) is often claimed to improve crop yields. Oldfield et al. 2019 tests that claim with a global meta-analysis of maize and wheat. They find higher SOC is associated with higher yields, up to ~2% SOC. They then look at the ~2/3 of global maize and wheat lands below 2% to estimate the opportunity to improve yield by boosting those soils to 2% SOC. Globally they estimate that we could produce ~5% more maize and ~10% more wheat, which represents 32% of the global yield gap for maize (largely in the US), and 60% for wheat (largely in China). Check out Figure 4 for global opportunity maps. Note that there is a lot of variance in the data, and it's even possible yields could decline slightly as SOC increases.
Vermeulen et al. 2019 is a call to action on improving global soil carbon stocks. It reviews some of the challenges that have impeded action at scale,and emerging opportunities that could give soil initiatives a boost. They call out three key needs, and look at possible actions to advance all three. First, a compelling vision for action led by political champions. Second, a stronger business case (including evidence of success for both public and private investors). Finally: a more compelling value proposition for farmers and land managers. They also highlight the need for practical measurement protocols, and several policy gaps. It's a quick read at 3 pages so worth a look.
Oldfield, E. E., Bradford, M. A., & Wood, S. A. (2019). Global meta-analysis of the relationship between soil organic matter and crop yields. SOIL, 5, 13–32. https://doi.org/10.5194/soil-2018-21
Tenopir, C., King, D. W., Christian, L., & Volentine, R. (2015). Scholarly article seeking, reading, and use: A continuing evolution from print to electronic in the sciences and social sciences. Learned Publishing, 28(2), 93–105. https://doi.org/10.1087/20150203
Vermeulen, S., Bossio, D., Lehmann, J., Luu, P., Paustian, K., Webb, C., … Warnken, M. (2019). A global agenda for collective action on soil carbon. Nature Sustainability, 2(1), 2–4. https://doi.org/10.1038/s41893-018-0212-z
p.s. as a reminder, you can search all of the science articles written by TNC staff (that we know of) here http://www.conservationgateway.org/ConservationPlanning/ToolsData/sitepages/article-list.aspx
(as you publish please email email@example.com to help keep this resource current). This will be my last plug for this resource since I'm leaving TNC.
If you'd like to keep track of what I write as well as what I read, I always link to both my informal blog posts and my formal publications (plus these summaries) at http://sciencejon.blogspot.com/
Tuesday, February 26, 2019
After 13 years as some form of scientist at The Nature Conservancy (TNC), I’ve learned a lot. Here are a few of my top lessons learned that are easy to miss when you’re focused on your core responsibilities. There are many ways to be a successful applied scientist; please share your own advice in the comments about what you have learned that I left out. Also, I recognize that these all take time and can add work. So don't be afraid to say no to requests to free up time to do things like this that you may not get asked to do!
1. Always make time to learn
Knowledge is the primary currency of scientists. If you don’t make time for learning, you’re withdrawing on an account that won’t replenish. Dedicating even a small amount of time to learning is essential to staying effective. I spend ~1-2% of my time reading scientific literature: enough to get through several papers each month and summarize them. I also spend a few percent working on diversity & inclusion issues at TNC, which has helped me learn on completely different topics. Hate reading papers? Call trusted colleagues to pick their brains, attend a webinar, or take a training on something you’re bad at. I was terrible at written and spoken communications, as well as conflict management, when I started at TNC. I’ve improved a lot by putting in effort. Don’t have time? Read papers on planes, trains, and buses (I do this on a tablet synced to Box), while eating breakfast, or when you need a break from email and talking to people. Pick a couple of your least productive standing meetings, switch from 60 to 30 minutes (or cancel), and use the time saved for learning.
2. Don’t be afraid to speak up for science and rigor
Scientists need to advocate for the use of evidence in making decisions. That can at times mean pushing for measures, providing internal critique and suggestions to statements by colleagues who aren’t as current with the science, and in general helping to ensure your organization is well aligned with good science. That can be uncomfortable, and many of us are reluctant to speak up. But I find that most of the time, when I raise concerns thoughtfully and back them up with science, people I work with have appreciated it (even when I disagree with them). I’ve even had senior managers complain to me that people are too reluctant to push back on them sometimes!
3. Step up to solve problems when you can
You likely sometimes run into a problem that you know has a relatively simple fix but which is not your job. Consider stepping up to fix it anyway. There have been several times when I’ve been annoyed by (and affected by) a problem and realized that I could make a big dent in it with just a few days of work. People see this as leadership, and it pays off. Examples could include working with a colleague in IT to rapidly put together a simple information system or web page; helping to organize or connect scientists on a topic who are currently not talking to each other; engaging with Employee Resource Groups on projects to improve diversity, equity or inclusion; or doing whatever else inspires you. Always thank the people who go out of their way to help you on these projects – a little recognition and appreciation goes a long way.
4. Network (internally and externally)
At a big NGO like TNC, there are guaranteed to be several staff who can help you learn and grow in your job (as well as be fun to work with). But, especially for field scientists, it can be hard to connect with others. Find out who works on your topic in other programs, and build a network of people you can ask to collaborate on papers, review your work, help brainstorm, etc. You can do it via Connect or Workplace, or via email and phone.
This applies outside of your organization too, especially if you’re at a smaller one. Mentoring students at universities (e.g. via NatureNet) is one great way to do this – you build connections with both the student and their academic mentor. I’ve also found that authors of scientific papers are almost always thrilled to be contacted with questions or feedback. I also have a policy of making time (15-30 minutes) for anyone who wants to connect with me; you never know how you can help them and vice versa. That includes folks in non-scientific roles (e.g. admin or operations) – they play a critical role in getting things done and are sometimes brushed off by busy scientists when they have questions. It also means being an ally for people who need it. Finally, look for ways to get to know decision-makers! Sometimes I’ve been invited to a non-scientific event to represent TNC, gone resentfully, and walked away with invaluable contacts I didn’t expect.
5. Learn your biases and reflect on them often
We all have bias and a perspective that informs how we do science. Many of us have strong opinions backed up by considerable reading and thought, so it can be hard to acknowledge that we almost always have bias, and that there’s a lot we don’t know. Pretending you can 'cure' bias means you'll likely be blind to it - focus on understanding it and mitigating it instead.
I try very hard to follow advice from Ray Bradbury, which is that whenever I notice myself having an emotional reaction to something I’m reading, I pause and think about why I’m reacting. For example, if I’m reading a paper that contradicts what I think I know, I work extra hard to ask “How could this be right? What assumptions am I making? How could I reconcile conflicts between this information and other information I have?” Sometimes careful science lands you in the same place as your gut. But take the time to be sure, and disclose your leanings to colleagues so they can help to bring other perspectives that balance yours.
Talk to people in other scientific camps, and listen to them in order to gather data, understand, and reflect (not to win an argument). Seek collaborators who disagree with you. This also includes listening to non-scientists who push back on recommendations by scientists about how much time and data we need to answer a challenging question! Most scientists prefer to answer questions with “it depends,” and sometimes we need to be pushed to provide actionable information or risk missing a chance to impact a decision.
6. Pay attention to your colleagues’ style
While it’s obvious, the fact that others think and feel very differently from you is surprisingly non-intuitive to me. I remember working with a colleague years ago who was consistently making mistakes on a process, and I added more and more detail to the guidance to try and fix it. But for him (and many others), as guidance gets longer, they read less of it. I had to understand his style and adjust accordingly. Similarly, I like to resolve issues through rapid back and forth discussion, but others don’t think that way, and instead need materials in advance and then time to think before responding. The “interaction styles” training is very helpful for this, as is the Enneagram. Learning the styles of some key colleagues who I don’t intuitively understand has been critical for me to build relationships and work effectively.
One final note - I found the photo in this post hilarious and used it for years at work (it was taken mid-dance at my wedding). But I learned that a couple of colleagues took it as a lack of seriousness or credibility, and once I learned it undermined my work with some people, I changed it. So pay attention to how some of your non-work choices impact your work, and reflect on when to bend (e.g. pick a more professional photo or username), and when to stick to your guns (I still haven't cut my hair).
Wednesday, February 20, 2019
It seems bizarre, but it's surprisingly hard to agree on what should count as a forest, or deforestation. If we can't agree on what deforestation is and how to measure it, we can't stop it. I wrote a blog post about this surprising problem for Mongabay:
How many trees make a forest?
It explains the issue, and why The Accountability Framework (a coalition of NGOs providing guidance on how companies can set and implement credible deforestation-free commitments) is so critical to solve it.
Friday, February 1, 2019
Here are some articles focused on genomics, but with a few others on deforestation, ecosystem services, and sustainable agriculture. The photo above of needle ice in my backyard is totally unrelated, but I'd never seen or even heard of it, and I found it super cool. Read about it on wikipedia!
Let me know if you need a copy of any of these articles. If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon
Jokpe & Schoneveld 2018 is a close look at zero-deforestation commitments (ZDC) by 50 influential corporate "power brokers." They identify several problems with implementation gaps and externalities. In particular they note that a lack of traceability and transparency about where commodities are sourced from makes verification difficult (and most companies rely on asking their suppliers to honestly self-report deforestation). They also report that 3/4 of companies with ZDC don't require company wide commitments from suppliers (so those suppliers can just sell deforestation linked products to other companies who don't care). This one is long but worth reading for breakouts by sector and other useful info. Note that TNC in this article refers to transnational companies and not The Nature Conservancy. The problems and gaps identified are things we're hoping to address with the Accountability Framework (https://accountability-framework.org/), which should be formally launched this spring.
There are many methods and tools to assess ecosystem services. Neugarten et al. 2018 is a report reviewing 9 assessment tools (EST, PA-BAT, TESSA, ARIES, C$N, InVEST, MIMES, SolVES, and WW) and providing decision trees on how to pick the right one for a given need. This is a fantastic reference for anyone working with ecosystem services, and it covers both written guidance documents and modeling tools. They recommend you identify the analysis question or need and think hard about expertise and resources you have to do the analysis before selecting a tool.
GENOMICS / GENE EDITING / GENETIC ENGINEERING:
Photosynthesis in plants relies on an enzyme called RuBisCO, sometimes called 'the most incompetent enzyme in the world' due to its inefficiency and energy loss during respiration. South et al. 2019 present a new transgenic GMO tobacco plant which improves the efficiency of respiration. As a result, their best modified tobacco plants had 41% higher biomass (including 33% more leaf biomass but also larger stems). It's not clear how much of the biomass gain could be translated to improved yields for grains or other crops, but that's still a potentially huge step forward which should be further explored. Eisenhut & Weber 2019 is a nice very short (1.5 page) summary of the article, and you can also read a blog about it here which includes some nice diagrams: https://phys.org/news/2019-01-scientists-shortcut-photosynthetic-glitch-boost.html
Kofler et al. 2018 is an editorial on benefits and risks of altering the DNA of wild organisms via gene editing. They call for collective oversight to ensure careful thought is given to environmental, social, and ethical concerns, and especially to local community involvement in each decision to potentially release an edited organism (as well as international bodies like IUCN). They stress that "using this technology irresponsibly or not using it at all could prove damaging" - and give good examples of each.
Sprink et al. 2016 looks at regulation of gene editing, and the difference between a process based approach (where the key factor is how an organism was modified) vs a product based approach (where the outcome is the key factor regardless of the process used). They argue that the European approach is outdated and doesn't reflect the continuum of modern technology (including several different applications of gene editing). They also dive into a legal argument of why it should be changed, and how it compares to the US and other countries. They make a good argument that regulation should be based on a genetic trait and product rather than the process used to develop it. This one is complex and wonky but a good reference, especially box 1 with definitions of several gene editing approaches.
Halewood et al. 2018 is an overview of how CGIAR is looking to use crop genome sequencing to drive more crop diversity and find crop traits that can deliver better outcomes for people and nature. Most readers can safely skip information on specific molecular markers (e.g. Table 1) but should read page 372 which lists several applications of gene editing technology and genotyping.
Zhong 2019 looks at how soy genotype and rhizobium inoculation (of seed or soil) impact plant growth, soy nodulation (the nodules help them fix nitrogen via bacteria), and microbiome. They found that the microbiome of soy varies depending on the genotype of soy. In particular whether the genotype forms high or low numbers of root nodules. Low-nodulation soy had more co-occurrence of the taxonomic groups (a more connected network) than the high-nodulation soy (figure 4). Both genotypes had their microbiome network connections increased by inoculation. The efficacy of the inoculant varies depending on plant genotype. See figure 1c / 1d for details. Low-nodule soy got a significant boost in nodulation from inoculation, but still had fewer nodules than high-nodule soy (for which nodulation was unaffected by inoculation). Both genotypes of soy got a roughly similar growth boost from inoculation. This means that to evaluate biological seed treatments / inoculation we have to look at the intersection of the inoculant, plant genetics, and baseline soil microbiome.
Eichler Inwood et al. 2018 is a thoughtful review of several different frameworks to assess agricultural sustainability (in different contexts and scales). Table 4 is a nice summary of the 9 frameworks they cover, with Table 5 providing more details on how and where they work. None are ideal in every context. Thy conclude with recommendations about how to select a framework (see Table 6 for properties they should have), choose indicators, collect data etc.
Eichler Inwood, S. E., López-Ridaura, S., Kline, K. L., Gérard, B., Monsalue, A. G., Govaerts, B., & Dale, V. H. (2018). Assessing sustainability in agricultural landscapes: a review of approaches. Environmental Reviews, 26(3), 299–315. https://doi.org/10.1139/er-2017-0058
Eisenhut, M., & Weber, A. P. M. (2019). Improving crop yield. Science, 363(6422), 32–33. https://doi.org/10.1126/science.aav8979
Halewood, M., Lopez Noriega, I., Ellis, D., Roa, C., Rouard, M., & Sackville Hamilton, R. (2018). Using Genomic Sequence Information to Increase Conservation and Sustainable Use of Crop Diversity and Benefit-Sharing. Biopreservation and Biobanking, 16(5), 368–376. https://doi.org/10.1089/bio.2018.0043
Jopke, P., & Schoneveld, G. C. (2018). Corporate commitments to zero deforestation: An evaluation of externality problems and implementation gaps. Occasional Paper 181. Bogor, Indonesia: CIFOR.
Kofler, N., Collins, J. P., Kuzma, J., Marris, E., Esvelt, K., Nelson, M. P., … Schmitz, O. J. (2018). Editing nature: Local roots of global governance: Science, 362(6414), 527–529. https://doi.org/10.1126/science.aat4612
Neugarten, R. A., Langhammer, P. F., Osipova, E., Bagstad, K. J., Bhagabati, N., Butchart, S. H. M., … Willcock, S. (2018). Tools for measuring, modelling, and valuing ecosystem services: guidance for Key Biodiversity Areas, natural World Heritage sites, and protected areas. (C. Groves, Ed.). Gland, Switzerland: IUCN. https://doi.org/10.2305/IUCN.CH.2018.PAG.28.en
South, P. F., Cavanagh, A. P., Liu, H. W., & Ort, D. R. (2019). Synthetic glycolate metabolism pathways stimulate crop growth and productivity in the field. Science, 363(6422), eaat9077. https://doi.org/10.1126/SCIENCE.AAT9077
Sprink, T., Eriksson, D., Schiemann, J., & Hartung, F. (2016). Regulatory hurdles for genome editing: process- vs. product-based approaches in different regulatory contexts. Plant Cell Reports, 35(7), 1493–1506. https://doi.org/10.1007/s00299-016-1990-2
Zhong, Y., Yang, Y., Liu, P., Xu, R., Rensing, C., Fu, X., & Liao, H. (2019). Genotype and rhizobium inoculation modulate the assembly of soybean rhizobacterial communities. Plant, Cell & Environment. https://doi.org/10.1111/pce.13519
p.s. as a reminder, you can search all of the science articles written by TNC staff (that we know of) here http://www.conservationgateway.org/ConservationPlanning/ToolsData/sitepages/article-list.aspx
(as you publish please email firstname.lastname@example.org to help keep this resource current).
If you'd like to keep track of what I write as well as what I read, I always link to both my informal blog posts and my formal publications (plus these summaries) at http://sciencejon.blogspot.com/
Wednesday, January 2, 2019
Happy new year!
Resolved to try harder to keep with science? Why not start with some of the best papers from last year that you may have missed? This month I picked my favorite 15 articles that I reviewed in 2018, plus a few other resources. A few were published earlier, but I read them all last year. I picked some because of importance, others because they were interesting, and two plug my own work.
There is one new article I couldn't resist mentioning, which is about the Camboriú water fund that I worked on. Kroeger et al. 2019 talks about how the water fund was designed, including estimating the impact it would have on land use change and water quality. We were able to show that it provided a positive financial return on investment after 44 years (if you include some modest societal co-benefits like flood control and biodiversity). PDF available here until ~Feb 10 after which an unformatted PDF is available here.
I also wanted to once again plug a cool resource to help you figure out which journal to submit a paper to: http://jane.biosemantics.org/ You enter the title and abstract of your paper and it gives you a list of appropriate journals. You may also want these tips on how to write an abstract to get found easily in Google and Google Scholar: https://authorservices.wiley.com/author-resources/Journal-Authors/Prepare/writing-for-seo.html and my blog on how to ensure all of your own research is viewable by others: http://sciencejon.blogspot.com/2018/03/tips-for-helping-people-to-find-your.html
Finally, my wife's comment on my book chapter on global agriculture land use trends (that there was no clear key take-away point) has stuck with me as a reminder of how important it is to get input from non-scientists on science writing. Here's a short blog where I tried to supplement the chapter: http://sciencejon.blogspot.com/2018/01/take-2-what-i-wish-id-put-in-my-recent.html
Carvin et al 2018 is a study I've been eagerly awaiting for years. It is a rigorous paired watershed study looking at the impact of a carefully targeted set of agricultural interventions, and is one of the first papers in the US to show we CAN improve water quality at a watershed scale (50 km2) through shifting ag. Initial work had found 9% of the area was contributing 40% of the phosphorous load, so the authors really targeted those heavy contributors. They found a 55% reduction in phosphorus runoff loads and suspended sediment event loads decreased by 52% for events during unfrozen soil conditions into the Pecatonica River tributary during storm events. This is big news as these outcomes have been elusive. However, this watershed was picked as one of the most likely to respond well, and those seeking to replicate these results should also carefully select their watersheds. Contact Steve Richter at TNC for more info.
Cui et al 2018 reports on the results of an ambitious study that worked with 21 million farmers (!) of maize, rice, and wheat over 10 years. China currently has some of the least efficient farms in the world, presenting a huge need to improve. This study used a soil & crop management framework that resulted in ~11% improved yield while reducing N application by ~16% (and reactive N losses by ~25%), and GHGs by 14-22% depending on crop. The scale is impressive: altogether they influenced 37.7 million ha. Interestingly, extension staff impacted over 10 times the area per staff person (471 ha / person) compared to agribusiness partners (see Fig 2). Regardless, this is good news in showing that it's possible to achieve "win-win" outcomes at scale even with smallholders. On the other hand, nitrogen efficiency is so poor in China, that much larger changes are needed to bring them in line with world averages, let alone truly sustainable targets (highlighting that policy changes are likely needed as well). Fig 1 has a great breakdown of impacts by crop and region.
Almost everyone who works for or closely with The Nature Conservancy heard about the 2017 "Natural Climate Solutions" paper (Griscom et al. 2017, I reviewed it in November 2017). If you've been waiting for the sequel - good news! Fargione et al. 2018 just provided a similar analysis specifically for the United States. It's short, excellent, and worth reading, but if you're impatient skip to Figure 1. That summarizes the potential of each pathway and splits out how much is achievable at different carbon prices. They found a maximum potential of 1.2 Pg (aka 1200 million metric tons) CO2e / yr (21% of current US emissions and ~27% of 2005 emissions), and ~300 Tg (million metric tons) achievable at $10 / t CO2e (~5% of US emissions). The biggest low cost opportunities are in planting cover crops followed by forest management, avoided habitat conversion, and improved farm nutrient management. You can read more about it on TNC's web site at https://www.nature.org/en-us/explore/newsroom/natural-climate-solutions-study/ or at https://eurekalert.org/pub_releases/2018-11/cu-nsr111418.php
Fisher et al. 2018 ("Knowledge diffusion within a large conservation organization and beyond") looks at how people find information about innovations and share them, specifically the spread of Conservation by Design 2.0 (CbD 2.0). We review how earlier versions of CbD spread from TNC (looking at published science articles and expert interviews), then use tons of varied data to look at CbD 2.0. I wrote a blog about the paper here: http://sciencejon.blogspot.com/2018/03/share-good-news-paper-on-improving.html
and the full paper is at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0193716
but here's a summary of what we learned:
- Sending repeated broadly-targeted communications (e.g. all-staff email / newsletters / etc.) that make it easy for recipients to find out more worked better than more narrowly focused communications (e.g. plenary talks, emails from executives).
- Expert interviews revealed several factors to promote diffusion: bringing in partners early to develop and test methods, committing up front to sustain support for the planning methods, having in-person workshops, using peer-review and shared learning, providing financial support, explaining how the methods address existing needs planners already have, and the existence of a support and learning network like the conservation coaches network (CCNET).
- Organizations may wish to use internal data to identify staff likely to play a key role in diffusing so that they can encourage that process (the paper has details on how, with more forthcoming in an upcoming paper)
- Working with academics on publications represents a potential way to get the word out with relatively low effort for organizations (academics I have worked with in other contexts are often very interested in data no one else has access to, and have published cool papers from those data).
- For scientists interested in this topic, we learned a lot about how to study knowledge diffusion, and share tips for researchers (e.g. thinking about image-blocking, legal and privacy constraints, distinguishing internal and external website visits, etc.).
Fisher & Kareiva 2019 (still in press) is a book chapter about sustainable agriculture that I write a few years ago. The first half is OK but is out of date and was written when I knew far less about agriculture. I'd skip to the 2nd half (start with the "Can Corporate Sustainability reporting be a force for improved agricultural practices?" section). There's some interesting content I haven't seen anywhere else on corporate sustainabiltiy and food labels. The chapter is available from: http://fish.freeshell.org/publications/FisherKareiva_CUP_2018_preformatted.pdf
Garnett et al. 2017 ("Grazed and Confused") is a very thoughtful review of the climate change / GHG impact of ruminants (largely cattle). Their first key findings is that even with good grazing ruminants still have high net GHG emissions. They also note sequestering soil carbon often has trade-offs with methane and nitrous oxide. Finally, as demand for animal protein rises sharply there is likely to be both land conversion and increasing GHGs as a result. These have all been reported widely in other studies, but it's a nice summary. On the one hand, it's hard to pull out quantitative results from this paper. On the other, it does a great job of covering the various arguments and counterpoints around cattle and carbon, and presenting the data in a value-neutral tone. Anyone interested in this topic should at least skim the 8-page summary.
Given how much research there is on trying to get crops to fix their own nitrogen, the finding by Griesmann et al. 2018 that many plants have lost the ability to fix N blew my mind. By comparing genomes of N-fixing plants to those that don't, they were able to find that ~3/4 of the species in their sample that didn't fix N had an ancestor that could! They suggest that the fact this ability has been lost multiple times reflects that plants spend a lot of energy to support N fixation, and that when N levels are adequate in the soil they eventually can lose the ability to fix it. In other words, as we try to engineer plants to fix their own N, it's worth reflecting on the costs that may have led plants in the past to reject this evolutionary path.
There's a blog on this one at http://www.sciencemag.org/news/2018/05/many-plants-need-bacterial-roommates-survive-so-why-do-some-kick-them-out
Hansen et al 2018 is a cool paper using empirical data to test how effective wetlands in the Minnesota River basin are at reducing nitrates in an ag landscape compared to cover crops and land retirement. They compared river water quality at ~200 sites under different flow conditions to high-resolution data on wetlands and land use to map correlations (they didn't get at true causation). They found wetlands were 5 times more effective per unit area at removing nitrates compared to cover crops and land retirement (although it's much harder to make a business case to a farmer around wetland creation). They also found wetlands strategically placed to intercept as much flow as possible were much more effective (see Fig 4 - the concept is obvious but the numbers are interesting). All these findings align well with prior work emphasizing the critical role of well-placed wetlands to improve water quality. If you read this paper watch out for the term "crop cover" (% of a given site area used to grow crops) as opposed to "cover crops" (presence of an additional crop on farmland that would otherwise be fallow for part of the year), as they're not super clear how they use the two terms.
Klein et al. 2007 is a fantastic reference examining dependence on animal pollination across 115 major crop species (ignoring crops like corn which are entirely wind-pollinated). I mainly use Appendix 2, which for each crop lists how much it benefits from animal pollination (from entirely dependent on animal pollinators like cocoa or squash, to receiving almost no benefit) as well as listing the type of pollinator, pointing to references, etc. While the appendix is my favorite part, they also note in the main paper that a) non-insect pollinators (e.g. birds and bats) are less well studied and b) as agriculture intensifies wild pollinators are likely to decline. This means thinking about pollinator habitat in and around farms can be important for some crops, and the appendix can identify which ones are most likely to see more benefit.
Nevle & Bird 2008 is grim but fascinating. They find a connection between seemingly unrelated factors: global CO2 levels and pandemics among indigenous people in the Americas brought on by European contact. They link the population crash to a reduction in burning of forests for swidden agriculture, subsequent forest regrowth storing ~5-10 Gt carbon, and argue this is a likely contributor to a small measured reduction in global atmospheric CO2 at the same time. It's more of an interesting hypothesis with data which is consistent than real 'proof' but it's still a fascinating (if depressing) read.
Rasmussen et al. 2018 is a global review of whether or not agricultural intensification is good for both people and the environment. While they find income and food production generally go up, ecosystem services go down in most cases. The figures have great summaries of results by geography, by metric of ecosystem services or human well being, and by separating 'win-win' cases from 'lose-lose' and mixed results in different contexts. The specific case studies are very interesting and thought provoking. Surprisingly, increased inputs were more likely to lead to win-win outcomes, with crop changes as reduced fallow more likely to lead to lose-lose. This is a relatively understudied area (this paper summarizes 53 studies) given the importance of intensification strategies; the lack of evidence for consistent positive outcomes doesn't mean intensification CAN'T work, but shows more work (design and monitoring) is needed to ensure we succeed in our goals. See https://www.scidev.net/global/agriculture/news/intensified-farming-rarely-aids-wellbeing-environment.html for a blog on the subject.
Springmann et al. 2018 asks what it would take to sharply reduce the impact of global food production by 2050 (and stay within resource constraints) without simply offsetting impacts like GHGs through reforestation or other mitigation. They look at 3 options (diet change, tech and management, and reducing food waste) across 5 aspects: GHGs, fresh water use, land use, nitrogen, and phosphorous. They key finding is that no one category of solution is enough, and that for GHGs in particular major diet change (towards mostly plant based foods) would have to be part of the solution. Figure 3 summarizes this set of scenarios nicely. With their medium ambition scenario, they find halving food loss and waste improves impact 6-16% (relative to 2050), improving tech and management reduces impact 3-30%, and modest diet change improves 5-29% (see Figure 2), or they could all be combined for a 25-45% reduction. Note that their findings are global averages, and some places will deviate considerably (e.g. they find nuts and seeds don't account for much overall water use, but in places like California they have a big water footprint). Check the methods for country-level data. You can read two articles about this study here: https://www.washingtonpost.com/health/2018/10/10/how-will-or-billion-people-eat-without-destroying-environment/ and here: https://www.theguardian.com/environment/2018/oct/10/huge-reduction-in-meat-eating-essential-to-avoid-climate-breakdown
For over a year now, TNC staff have been hearing about a science analysis asking whether it's possible for both people and nature to thrive (in a shared conservation vision). Tallis et al 2018 is the newly available science paper behind that analysis. It compares two 2050 global scenarios: business as usual (BAU), and one designed to improve human and environmental outcomes (Sustainability). The latter would result in 577 million ha more habitat than BAU, while limiting climate change, improving air quality, and more. It doesn't assume we can drastically change diets, and sticks with biophysical constraints, but it does recognize that there are major social, economic, and political barriers to making the sustainability scenario a reality. The discussion has several thoughtful limits and caveats, but it's still exciting to see what is at least possible, if not easy to achieve. You will have to read the supplemental material to get a good sense of the work, but the main paper is conveniently short. One final note is that they assume climate change won't impact ag much in either scenario, which is optimistic. You can read all about the paper and its findings here: https://www.nature.org/en-us/what-we-do/our-insights/perspectives/the-science-of-sustainability/?vu=r.v_twopaths
VanZanten et al. 2018 is a really thoughtful paper that takes a refreshing approach to looking at the environmental impact of animal foods in our diet. They note that while using arable land to feed livestock (rather than directly feeding humans) is inherently inefficient, there are some grasslands, food waste, and food by-products like distillers grains that humans can't eat. So to minimize land used to feed the world, ~10% of calories (& ~1/3 of protein needed) could come from animal foods. Fig 4 shows how animal consumption in different regions compares to the protein goal, and Fig 5 shows a similar breakdown for calories and other nutrients. They cover how different animals fit in (e.g. ruminants for grasslands, pigs for food waste, etc.), noted that GHGs are still higher in their scenario than an all-vegan diet, and cover several interesting caveats and twists. One thing they didn't mention - some of the underlying studies have a large role for milk, which people have trouble digesting in many places around the world. But is is a really well done paper and I highly recommend it.
Woodard & Verteramo-Chiu look at how much better the Federal Crop Insurance Program (FCIP) could perform if it used soil data to establish rates and coverage. In other words, how could FCIP incentivize soil health practices that would reduce risks and costs of the program, while avoiding perverse incentives (e.g. in the past crop insurance was not available to farmers using cover crops). It's a fairly wonky economics paper, but they make a good case for much errors and bias exist in the current program. The key finding is that farms with high-quality soils are generally overpaying, and low-quality farms are underpaying. See Fig 3 for an example of how strong the pricing erors are (up to a factor of 6). By accounting for soils data (and perhaps current practices), this program could be an important driver to get farmers to start rebuilding healthier soils to keep premiums low. They focus on top corn producing states where soil quality is relatively homogeneous; benefits of accounting for soil should be higher in regions with more varied soil. With predicted volatility from climate change, improving crop insurance will be increasingly important.
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