Friday, May 1, 2020

May 2020 Science Journal Article Summary

Tartine sourdough bread

Greetings,

I hope you're all staying healthy, well fed, employed, and finding ways to stay connected.

This month I am tackling science articles discussing the relationship between COVID-19 and conservation (plus a couple related ones on air quality). It's not a representative sample of the literature. I drew from 1) articles either sent to me directly or 2) articles cited (in email or twitter or blogs I ran across) to support high-level conclusions, and I reviewed the ones that seemed both the most relevant and relatively high-quality.

I also don't think I'm qualified to weigh in. But the topic is unavoidable, and I would rather make the attempt than ignore it. I was prompted partly by Bob Lalasz' excellent post "The Wrong Kind of Serenity," even though I don't know if my expertise is sufficient to the task.

Most of the blogs and emails I've seen on this topic either seem to be in support of a clear agenda, or were written for a constrained audience and can't be shared. I especially welcome your feedback and perspectives on both this summary and the papers themselves. Please also send other papers & resources you have found the most useful (or problematic).

Overall, I didn't find a lot of consensus conclusions and recommendations. But there is agreement that the more humans (and our domesticated animals) live near to nature (especially when primates and bats are present), spend time in nature, and convert wildlife habitat (for settlements or food production), the more chance there is of being exposed to zoonotic disease (spread between animals and humans). It is also fair to say that reducing air pollution will have strong benefits to human health even if the potential link between COVID-19 mortality and poor air quality is not supported by additional research.

Finally, there is a lot of debate about whether higher biodiversity reduces the risk of disease transmission. The basic idea is that with more species there will be fewer compatible hosts for any given species. On the other side, as biodiversity declines some wildlife species prone to harboring zoonotic disease will be lost. I didn't read enough of this literature to come to an informed conclusion, but I'm not yet convinced. You can read a bit about it here (this article favors the idea that biodiversity loss worsens disease risk but includes a counterpoint): https://www.caryinstitute.org/news-insights/media-coverage/more-we-lose-biodiversity-worse-will-be-spread-infectious-diseases

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

CONSERVATION & HUMAN HEALTH:
DISEASE TRANSMISSION:
Smith & Guégan 2010 is a (long) summary of the origin and location of all human pathogens. It's useful context for thinking about COVID-19 and other zoonotic diseases. For emerging infectious disease in particular (diseases which are new or becoming more significant), about 3/4 of them are zoonotic. They also cite an earlier paper (Woolhouse & Gowtage-Sequeria 2005) that ranks the drivers of emerging pathogens (by # of pathogen species, NOT by impact), which from most to least spp. are: "(1) changes in land use or agricultural practices, (2) changes in human demographics and society, (3) poor population health, (4) hospital and medical procedures, (5) pathogen evolution, (6) contamination of food supplies or water sources, (7) international travel, (8) failure of public health programs, (9) international trade, and (10) climate change." Land-use change has been more key for bacterial and zoonotic disease, and mostly involves people coming into closer contact with nature and wildlife.

Morse et al. 2012 offers ideas from the past to predict and prevent the next zoonotic pandemic. It has a useful summary of how these pandemics emerge (see Panel 1), and Figure 1 has a global risk map which could inform monitoring. However, we have never predicted a pandemic before humans became infected. They recommend continued improvement of global monitoring to quickly identify novel pathogen outbreaks, while noting this has been a top recommendation for decades. Other suggestions seem impractical (better sanitation and biosafety practices in potential hotspots) or too expensive and complicated. For example, modeling which wildlife species are most likely to harbor emerging zoonoses (zoonotic diseases) would enable better monitoring. But there are thousands of potential pathogens to evaluate. The PREDICT program (from USAID) is listed as an example of a successful approach (combining collecting samples from wildlife and identifying the pathogens posing the most potential risk). Ironically the program ended fieldwork in September 2019, and was ended in March 2020 before being given an emergency 6-month extension in April 2020. It will be interesting when later analysis reveals whether or not they had the data needed to predict the emergence of SARS-CoV-2 / COVID-19.

I skimmed quite a few articles on the "dilution effect" arguing that higher biodiversity leads to lower disease risk before settling on Ostfeld & Keesing 2012 to review here. I like that they are methodical in exploring the issue, but it's a long article. I found the first half fairly unconvincing: modeling 'adding diversity' yields different results than much more likely cases of losing diversity, and the agricultural example doesn't apply well to zoonoses. But starting with p10 of the PDF (p166) there are useful case studies showing that diseases w/ generalist animal hosts like rodents will tend to be higher risk as diversity goes down. But despite showing biodiversity loss can raise disease risk, on p19 of the PDF (p175) they cite a metaanalysis finding that species richness had very little effect on zoonotic disease emergence. Instead human population density was the key factor. I look forward to reading more on this topic to have a more informed opinion.

Johnson et al. 2020 is a timely analysis of which mammals have the most potential to transmit disease to humans (estimated by the number of zoonotic virus species, an imperfect but useful proxy). Overall, the more common a species was, the more viruses they shared with humans. Domesticated mammals (12 species) were the highest-impact variable in their model, and they hosted 50% of all zoonotic virus species (not necessarily exclusively). 75% of virus species were hosted by either rodents, bats, and/or primates. Primates and bats host more viruses per mammal species, and bats in particular have traits that make transmission to other species more likely (rodents are significant partly because there are many common rodent species who live near humans). Finally, while they note that among threatened species virus richness goes up when the mammals are threatened by habitat loss, those species still have fewer virus species than more common mammals.

Faust et al. 2018 models how different rates and amounts of habitat loss impact the risk of zoonotic disease. The primary finding is intuitive: risk is fairly low when habitat loss is either very low (few humans in contact w/ nature) or very high (few wild populations in contact w/ people). So it's the mix of humans and natural habitat that poses more risk. In general, faster land conversion reduces exposure and thus risk. However, they note that fast conversion can also rarely lead to the largest outbreaks (where a lot of displaced species interact with a large pool of human hosts who are likely to mix with other humans). Figure 2 has interesting case studies of zoonotic diseases with different transmission modes, and Figure 5 shows how infection rates vary over time depending on rate of habitat loss.

Bloomfield et al 2020 asks what factors are associated with physical contact between humans and wild nonhuman primates (and thus potential concerns with disease exposure). They looked at smallholder farmers in Uganda living near forest patches (which they call "core") in an area with ongoing deforestation to create new farms and pastures (which along with settlements they call "matrix"). The results are not surprising: people who go to forests (for hunting & foraging for food, and/or gathering small trees for construction) or live in areas with more forest fragmentation have slightly higher chances of contacting primates.

Mills et al. 2010 summarizes the scant information on how climate change can affect zoonotic disease. They list four ways climate change can impact vector-borne zoonotic disease via changes to the host and/or vector: range shifts that result in contact w/ new human populatoins, changes in population density (leading to more or less human contact), changes in prevalence of infection (leading to more or less contact w/ infection), and changes in pathogen load (leading to more or less chance of transmission per contact). They list case studies of each, and note that while there is evidence of climate change having increased risk, there are many confounding variables not accounted for. For example, despite the mosquito host of Dengue and Zika becoming established in Texas, the diseases remain relatively rare despite nearby epidemics in Mexico (the difference may be due to more air conditioning lowering exposure in Texas). They close with a research agenda for the kinds of studies most needed to better understand how climate will impact zoonotic disease.

How does migration impact the risk of zoonotic disease? Altizer et al. 2011 find that it's complicated. Migrations can spread pathogens including to other species. They can also increase risk via reducing host immune function, and increasing exposure to pathogens for the migratory species. But migrations can also cause disease risk to go down by leaving parasites behind (and making it harder for parasites to reproduce in their absence), or removing infected animals from the population (since they're not fit enough to migrate, which may also provide selection pressure favoring less virulent pathogens). On net, migration may be bad for specialist pathogens, parasites that build up over time, pathogens transmitted via biting vectors or intermediate hosts, and pathogens transmitted mainly from adults to juveniles during breeding. Migration may help generalist parasites where there are shared stopover areas or wintering grounds, or help specialist pathogens that spread better with dense populations common during migration.

AIR QUALITY:
While poor air quality is a leading global health risk, I've only seen one study so far directly looking at how it impacts COVID-19 mortality (and it's a preprint, so it hasn't been peer-reviewed yet). Wu et al. 2020 looked at correlation between long-term U.S. air quality (specifically PM2.5: tiny particles < 2.5 μm in diameter) and found that fairly small increased in PM2.5 concentration (1 μg/m3) were associated with a 15% increase in COVID-19 death rate (compared to a 0.7% increase in the rate of all-cause mortality). They control for quite a few confounding variables (e.g. hospital beds, population, obesity, smoking, poverty, etc.), but note that limited testing means they can't properly control for outbreak size (which could be the primary driver of their results). Initial discussion has identified some other missing variables (like accounting for respiratory diseases like COPD or lung cancer), but this is still a useful data set to inform discussions and more research. The authors are also report they are publishing similar results for China and Italy. It's not clear whether short term improvements in air quality from the lockdown would make any difference. There are interesting comments on the initial version of the paper.

Zhang et al. 2019 shows how many lives can be saved by reducing air pollution, using an initiative in China (2013-2017) as a case study. The authors estimate that "national emissions of SO2, NOx, and PM2.5 decreased by 59%, 21%, and 33%, respectively." This reduction in PM2.5 (by ~20 μg/m3) avoided ~410,000 premature deaths. They have lots of detail about all the actions that made this possible, and Fig 4 shows how much each change contributed to avoided deaths; the biggest contributions came from stronger industrial emissions standards and upgrades to industrial boilers. Note that this study was published pre-COVID-19, so doesn't include potential benefits of reduced complications from the disease (although even the reduced levels in China are still much higher than the US).

Tessum et al. 2019 is a very short but useful look at racial inequity of PM2.5 air pollution. It is also a great overview of sources and risks of PM2.5 (see Fig 1), which they note is responsible for about 2/3 of US deaths from environmental causes. But their key finding is that black and Latinx people are exposed to 56% and 63% more PM2.5 than the relative amount of pollution caused by the goods and services they consume. Conversely, non-Latinx white people & other races (they lump whites with Asians, Native Americans, and all other races) are exposed to 17% less PM2.5 relative to their consumption. From 2003-2015, overall PM2.5 exposure dropped ~50% on average, while inequity decreased for black people but remained similar for others. Given the findings of the Wu 2020 preprint (that PM2.5 exposure increases COVID-19 mortality), this disease could further racial inequity. However, to date the CDC has found that while COVID hospitalized patients are disproportionately black, that there are fewer Latinx patients than in surrounding communities, so there are clearly other factors at play.


REFERENCES:
Altizer, S., Bartel, R., & Han, B. A. (2011). Animal Migration and Infectious Disease Risk. Science, 331(6015), 296–302. https://doi.org/10.1126/science.1194694

Bloomfield, L. S. P., McIntosh, T. L., & Lambin, E. F. (2020). Habitat fragmentation, livelihood behaviors, and contact between people and nonhuman primates in Africa. Landscape Ecology, 35(4), 985–1000. https://doi.org/10.1007/s10980-020-00995-w

Faust, C. L., McCallum, H. I., Bloomfield, L. S. P., Gottdenker, N. L., Gillespie, T. R., Torney, C. J., … Plowright, R. K. (2018). Pathogen spillover during land conversion. Ecology Letters, 21(4), 471–483. https://doi.org/10.1111/ele.12904

Johnson, C. K., Hitchens, P. L., Pandit, P. S., Rushmore, J., Evans, T. S., Young, C. C. W., & Doyle, M. M. (2020). Global shifts in mammalian population trends reveal key predictors of virus spillover risk. Proceedings of the Royal Society B: Biological Sciences, 287(1924), 20192736. https://doi.org/10.1098/rspb.2019.2736

Mills, J. N., Gage, K. L., & Khan, A. S. (2010). Potential Influence of Climate Change on Vector-Borne and Zoonotic Diseases: A Review and Proposed Research Plan. Environmental Health Perspectives, 118(11), 1507–1514. https://doi.org/10.1289/ehp.0901389

Morse, S. S., Mazet, J. A. K., Woolhouse, M., Parrish, C. R., Carroll, D., Karesh, W. B., … Daszak, P. (2012). Prediction and prevention of the next pandemic zoonosis. The Lancet, 380(9857), 1956–1965. https://doi.org/10.1016/S0140-6736(12)61684-5

Ostfeld, R. S., & Keesing, F. (2012). Effects of Host Diversity on Infectious Disease. Annual Review of Ecology, Evolution, and Systematics, 43(1), 157–182. https://doi.org/10.1146/annurev-ecolsys-102710-145022

Smith, K. F., & Guégan, J.-F. (2010). Changing Geographic Distributions of Human Pathogens. Annual Review of Ecology, Evolution, and Systematics, 41(1), 231–250. https://doi.org/10.1146/annurev-ecolsys-102209-144634

Tessum, C. W., Apte, J. S., Goodkind, A. L., Muller, N. Z., Mullins, K. A., Paolella, D. A., … Hill, J. D. (2019). Inequity in consumption of goods and services adds to racial–ethnic disparities in air pollution exposure. Proceedings of the National Academy of Sciences, 116(13), 6001–6006. https://doi.org/10.1073/pnas.1818859116

Woolhouse, M. E. J., & Gowtage-Sequeria, S. (2005). Host range and emerging and reemerging pathogens. Emerging Infectious Diseases, 11(12), 1842–1847. https://doi.org/10.3201/eid1112.050997

Wu, X., Nethery, R. C., Sabath, B. M., Braun, D., & Dominici, F. (2020). Exposure to air pollution and COVID-19 mortality in the United States. MedRxiv, 2020.04.05.20054502. https://doi.org/10.1101/2020.04.05.20054502

Zhang, Q., Zheng, Y., Tong, D., Shao, M., Wang, S., Zhang, Y., … Hao, J. (2019). Drivers of improved PM 2.5 air quality in China from 2013 to 2017. Proceedings of the National Academy of Sciences, 116(49), 24463–24469. https://doi.org/10.1073/pnas.1907956116


Sincerely,

Jon

Wednesday, April 1, 2020

April 2020 Science Journal Article Summary

Cherry tree in bloom
Wow,

I'm guessing that most of you are reading more science while stuck at home, but that you're focusing on science related to the pandemic. I certainly am.

But for now, I figured I'd send the usual kind of summary (focused on protected areas this month), since this is where my expertise lies. I thought of reviewing some articles on how conservation can both help and hurt infectious disease transmission (depending on context), but that felt crass.

If you have thoughts on these summaries (if they should pause, change, etc. during the pandemic) please let me know. If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

PROTECTED AREAS:
Hannah et al. 2020 estimates that effectively conserving 30% of tropical land could cut predicted species extinction by ~1/2-2/3 (if the conserved areas are both cited ideally and managed well: this is not about legal protection alone). Conserving 50% could reduce extinction by more like 2/3-80% (see Table 1 for details including how this varies by region). This is useful to understand how effective conservation can be at different scales. But it's important to note that citing PAs in ideal locations continues to be elusive, this model relies on fairly simple assumptions using species-area curves, and the fact that the results didn't vary much with climate change (RCP2.6 vs RCP 8.5) is concerning. Nonetheless, this could be motivating to highlight the importance of protecting and managing enough of the right places on earth to slow species extinction.

How well does the current network of protected areas represent both biodiversity and the provision of ecosystem services in the tropics? Neugarten et al. 2020 has answers for five countries (Cambodia, Guyana, Liberia, Madagascar, and Suriname). They found that PAs are doing pretty well on biodiversity, forest protection, and forest carbon stocks, although with lots of room for improvement (Table 3). But PAs are not doing well on protecting non-timber forest products (like food and medicine) nor freshwater ecosystem services, both of which are mostly protected at about the same rate as land overall in each country (except Cambodia which did somewhat better on freshwater ecosystem services). Identifying opportunities to improve like this is critical to inform where to cite future PAs. They are up front about a few caveats: they looked only at designation of formal protected areas (rather than effective management on the ground), this may not be reflective of PAs across the tropics more broadly, and they had to rely on some squishy data (e.g. a mix of data sources and expert input to identify biodiversity priority areas). But it's still a good step to inform citing the next wave of PAs as interest in doing so ramps up across the globe. The authors have shared their data here: https://www.conservation.org/projects/mapping-natural-capital/mnc-data/ and are happy to help others to access and use it.

Wilhere 2008 makes an important point about analyses of how much conservation "is enough." He argues there's no single answer, since it depends on society's values for things like what risk of extinction is acceptable. Another key point is that the inputs into these models (which spp. or habitats to model and prioritize) are inherently value-driven as well. He recommends that these kinds of analyses: are transparent about the role of ethics / values (outside of science) in choosing conservation targets, recognize that any modeled policy options are only one of many possible choices, consider alternative targets to prioritize, and work with economists to produce cost estimates of any recommendations.

Wilhere et al. 2012 is a critique of one of the many 'half earth' papers arguing we need to effectively conserve at least half of the earth to avoid unacceptable biodiversity loss (Noss et al. 2012). The critique is similar to the Wilhere 2008 paper: the half earth target is presented as a "strict scientific point of view" without recognizing the value judgments that inform the results. They call for papers like Noss' to clearly articular the values of the author, and evaluate multiple policy options reflecting different values.

Finally, Armsworth et al. 2020 looks at  the best "bargains" exist for conservation: where the most species can be protected (from projected land conversion) for the lowest cost of land acquisition. In other words, how can we prevent the most species loss with a fixed budget for protection?
The new spatial prioritization model this is based on goes beyond binary models (which recommend protection or not), and instead allocates funding as a continuous variable. It also considers complementarity to avoid concentrating funding in areas rich with the same species. When they run the model for the coterminous U.S., attempting to conserve all species equally leads to the Southwest being a priority (since there's lots of cheap, intact habitat). But focusing on vertebrates vulnerable to extinction, priorities pop out in Texas (due to cave ecosystems with many unique & threatened species in small places) and the Southern Appalachians. There's a great discussion of how different assumptions and data inputs impact the results. There's a blog about this article here: http://www.nimbios.org/press/FS_conservetool

WATER USE:
Richter et al. 2020 has two key points about water scarcity (and the resulting impact on freshwater ecosystems) in the Western United States. First, cattle feed is the biggest driver - 1/3 of water consumed in 17 Western states is for cattle feed, and in the Colorado River basin it's 55% (Table 1). But in good news, there is a proven affordable solution - paying farmers to temporarily fallow (stop growing crops) some or all of their land used for cattle feed. We also would need to reduce some of the water transferred between basins to fully address the over-allocation of water. The paper also has good data on which cities are driving the most scarcity via demand for beef, impact of water scarcity on fish (including extinction risk), and the cost of payments to farmers for fallowing ($82-241 million / year). Finally, one of the authors (Arjen Hoekstra) passed away last year, and I wanted to express how much I appreciate his pioneering work on water footprinting, and how much influence he had on me as a scientist. He will be sorely missed.

MARINE ECOLOGY:
Hammerschlag et al. 2019 is a great overview of the many ecological functions and ecosystem services provided by aquatic predators (both marine and freshwater). It's well written enough to serve as a good introduction to the topic even for people like me with very little marine ecology background. Most of the benefits are fairly obvious, but benefits to climate mitigation (by reducing herbivores that can reduce carbon sequestration and storage) and inspiring products like boat coatings to reduce drag were especially interesting.

REFERENCES:
Armsworth, P. R., Benefield, A. E., Dilkina, B., Fovargue, R., Jackson, H. B., Le Bouille, D., & Nolte, C. (2020). Allocating resources for land protection using continuous optimization: biodiversity conservation in the United States. Ecological Applications, eap.2118. https://doi.org/10.1002/eap.2118

Hammerschlag, N., Schmitz, O. J., Flecker, A. S., Lafferty, K. D., Sih, A., Atwood, T. B., … Cooke, S. J. (2019). Ecosystem Function and Services of Aquatic Predators in the Anthropocene. Trends in Ecology & Evolution, 34(4), 369–383. https://doi.org/10.1016/j.tree.2019.01.005

Hannah, L., Roehrdanz, P. R., Marquet, P. A., Enquist, B. J., Midgley, G., Foden, W., … Svenning, J. (2020). 30% Land Conservation and Climate Action Reduces Tropical Extinction Risk By More Than 50%. Ecography, 1–11. https://doi.org/10.1111/ecog.05166

Neugarten, R. A., Moull, K., Martinez, N. A., Andriamaro, L., Bernard, C., Bonham, C., … Turner, W. (2020). Trends in protected area representation of biodiversity and ecosystem services in five tropical countries. Ecosystem Services, 42(January), 101078. https://doi.org/10.1016/j.ecoser.2020.101078

Richter, B. D., Bartak, D., Caldwell, P., Davis, K. F., Debaere, P., Hoekstra, A. Y., … Troy, T. J. (2020). Water scarcity and fish imperilment driven by beef production. Nature Sustainability. https://doi.org/10.1038/s41893-020-0483-z

Wilhere, G. F. (2008). The how-much-is-enough myth. Conservation Biology, 22(3), 514–517. https://doi.org/10.1111/j.1523-1739.2008.00926.x

Wilhere, G. F., Maguire, L. A., Scott, J. M., Rachlow, J. L., Goble, D. D., & Svancara, L. K. (2012). Conflation of Values and Science: Response to Noss et al. Conservation Biology, 26(5), 943–944. https://doi.org/10.1111/j.1523-1739.2012.01900.x


Stay safe, vigilant, and healthy,

Jon

p.s. 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/

Monday, March 2, 2020

March 2020 Science Journal Article Summary

Frozen waterfall


Greetings,

This month I've been focused on science practice and science writing (and some vacation) rather than science reading. So this is a mini-review with just three articles. Sorry!

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

CLIMATE CHANGE:
Sanderson et al. 2020 make a straightforward but often overlooked point about soil carbon and grazing lands. In semiarid rangelands (like the Western Great Plains in the U.S.), the best way to maximize soil carbon is to prevent rangelands from being converted (to farms, housing, etc.) rather than changing grazing practices. Soil C increases from management are typically small and variable, while soil C losses from conversion are large and consistent. They do a great job of making this point and explaining why it's true. The only caveat is that they focus on soil C and not total GHG balance; considering methane and nitrous oxide of both rangelands and alternative land uses makes the net GHG impact more complex.

PROTECTED AREAS:
Global estimates of % protection hide the fact that protection varies widely for different  cosystems and habitat types. Sayre et al. 2020 splits that up into 278 natural ecosystems (based on temperature, moisture, elevation, land cover, etc). If you limit protection to IUCN 1-4 (stricter protection), 9 of those 278 were totally unprotected and 206 were below 8.5% protected (half way to Aichi targets). If you use IUCN 1-6 (including  areas allowing more human use) only 1/3 of ecosystems are below 8.5%. Table 5 shows how much of each major land cover group (forests, grasslands, etc.) has been lost, Table 4 has the details for the 278 ecosystems. Some figures are easier to see online: https://www.sciencedirect.com/science/article/pii/S2351989419307231?via%3Dihub

OTHER:
I've been referring to the concept in Lehmann & Rillig 2014 for years but never actually reviewed it. Essentially they argue that we should distinguish between uncertainty and variation. Variation we can explain is not uncertainty: if we plant cover crops on 100 farms, and soil organic goes up in some and stays the same in others, but we can explain that with soil type and climate, it's not uncertainty. We just have to recognize that results will vary depending on a set of variables we can describe. Variation we CANNOT explain is uncertainty, e.g. if we run the same cropping experiment and farms with the same values for the variables we think are relevant still have different results, that represents uncertainty (that we don't yet know what drives outcomes). It's a useful framework in many context, for example the impact of conservation practices on water quality is extremely variable by context, but true uncertainty is fairly low.

REFERENCES:
Lehmann, J., & Rillig, M. (2014). Distinguishing variability from uncertainty. Nature Climate Change, 4(3), 153. https://doi.org/10.1038/nclimate2133

Sanderson, J. S., Beutler, C., Brown, J. R., Burke, I., Chapman, T., Conant, R. T., … Sullivan, T. (2020). Cattle, conservation, and carbon in the western Great Plains. Journal of Soil and Water Conservation, 75(1), 5A-12A. https://doi.org/10.2489/jswc.75.1.5A

Sayre, R., Karagulle, D., Frye, C., Boucher, T., Wolff, N. H., Breyer, S., … Possingham, H. (2020). An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems. Global Ecology and Conservation, 21(December), e00860. https://doi.org/10.1016/j.gecco.2019.e00860

Sincerely,

Jon

p.s. 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/

Monday, February 3, 2020

February 2020 science journal article summary

Ice crystals on windshield

Greetings,

This month is a mix of topics; some papers came out recently that were too cool for me to wait to review with other similar ones, and I couldn't resist plugging the latest paper I worked on (Hamel et al. 2020). If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

Also, a 12-minute video came out recently about the 2017 March for Science, and I show up in it a few times. It's called "SciComm: Raising Our Voice for Science and Public Policy," it's directed & produced by Larry Kirkman (larry@american.edu) and Shannon Shikles at the Center for Environmental Filmmaking at American University, and you can watch it here: https://vimeo.com/383209723


CLIMATE CHANGE:
Sippel et al. 2020 bucks the pattern where climatologists emphasize how distinct climate and weather are. Past research has shown the impact of climate change on certain weather events, but this paper actually detects the impact of climate change on any given day since late March 2012! By summarizing weather data all over the world, they found that we’ve been clearly outside of natural variability for the past 8 years on a daily basis. On a monthly basis, climate change has been detectable from global weather data since 2001. You can read a newspaper article about the paper at https://www.washingtonpost.com/weather/2020/01/02/signal-human-caused-climate-change-has-emerged-every-day-weather-study-finds/  I love the description of this paper from meteorologist Maria LaRosa: “[it’s] like looking closely at an impressionist painting –  you can't say what the picture is until you step back and look at the whole”


ECOSYSTEM SERVICES:
Chaplin-Kramer et al. 2019 produced global maps summarizing ecosystem services (sort of) for coastal protection, water quality regulation, and crop pollination, now and in 2050 (under three different scenarios). One twist is that they go beyond the usual definition of ecosystem services (benefits provided by nature and received by people who need them) to also look at the 'benefit gap' where there are people with needs nature is not currently meeting (see Fig 2, bottom row, pink / lavender color). There's a lot to explore here, but one finding is that both SE Asia and Africa are expected to have increasing gaps for all three services. There's plenty of uncertainty, but this is a great set of data to think about trade-offs under different future paths. You can explore their results in a web map at http://viz.naturalcapitalproject.org/ipbes/

Johnson et al. 2019 analyzed where it makes economic sense to protect undeveloped land within 100-year floodplains across the U.S. They compared  expected flood damages (over the next 30-50 years) to land acquisition cost (to prevent development and avoid damages). They found benefits exceeded acquisition cost for about 1/3 of unprotected natural areas, and that the strongest benefits were within the 20-year floodplain but outside of the 5-year floodplain. Compared to the 5-year floodplain, these areas are more likely to get developed even though they flood less often, leading to more potential damages. Figure 3 has a map of the counties with the highest benefit:cost ratio, focused in Appalalachia, Arizona, and a mix of other places. Note that buying undeveloped lands avoids the controversy associated with asking or forcing people already living within floodplains to move.

Brancalion et al. 2019 looks at opportunities to restore lowland tropical rainforests around the world. They evaluate both the benefits (including biodiversity, climate mitigation & adaptation, and water security) and feasibility (land opportunity cost, ecological uncertainty, and chance of forest persistence). Figure 2 shows where there's the most opportunity, both by area (Brazil) and by combined benefit and feasibility (Madagascar, Tropical Andes). Where to focus depends on your goal - the places with the most total benefits are generally less feasible (higher land costs and competition, e.g. areas where habitat loss is recent and ongoing). But Figure 3 shows several examples of countries with restoration commitments who appear to have large areas with relatively high benefits and feasibility.


LANDSCAPE ECOLOGY:
Fahrig 2017 & Fahrig et al. 2019 are challenging but important reviews on the ecological impact of habitat fragmentation at the landscape scale (big areas). Their key findings are that with the amount of habitat loss being equal, fragmentation per se typically (70% of the time) didn't significantly impact biodiversity or ecological function at all. Even stranger, when it did have a significant impact, 3/4 of the time it was positive (even for threatened and rare species)! Section 5 in the 2017 paper summarizes the different explanations that authors of the primary studies provided, from fragmentation boosting functional connectivity (by reducing distance between patches) to edge effects and others. She concludes that in most cases we confound habitat loss with fragmentation, and that most of the time our intuition (that fragmentation per se is bad) is incorrect. She also notes that authors sometimes bury or caveat their findings of positive effects of fragmentation, which is one reason her findings continue to seem so wrong. My key take-aways are: 1) it's very hard (but very important) to examine our biases and deeply held beliefs when reading contrary science, 2) there is a good case made in the 2019 paper that small patches are under-protected, given their importance in many landscapes.

Jones et al. 2019 used GPS collars to track both migratory and resident pronghorn, and to model what features they avoided and which they ignored. They found that pronghorn were very reluctant to cross fences (consistent with under studies - they tend to crawl under rather than jump over), and avoided roads, but mostly ignored oil and gas well pads. There's a lot of other findings in their model, but the one I found most interesting was the concern that if ranches add more fencing to allow rotational grazing, it could have serious negative impacts on pronghorn and  mule deer unless wildlife-friendly fences are used.


RESEARCH IMPACT:
Hamel et al. looks at how scientific information was perceived and used in decision making for a water fund in Brazil. Through interviews, we determined that the hydrological modeling and monitoring data was NOT used in designing and implementing the water fund. But counter-intuitively, having done the analysis using complex models and high-resolution data was seen as important for the water fund to be seen as scientifically credible. So ironically, even though the credible models were not actually used, their existence helped build support for the overall water fund. Despite this, as long as monitoring data was used to calibrate and validate the model, a simpler model (InVEST, as opposed to SWAT) and coarser data resolution (30m, as opposed to 1m) would have met the information needs of the users. We should have had more frank discussions up front with the ultimate users of the information to produce a model seen as credible and actually used, while avoiding over-investment in model complexity that wasn't needed.

Samanta et al. 2019 is a paper about a program in Michigan to improve water quality issues from agriculture via a really well thought out collaboration (w/ scientists, practitioners, universities, farmers, and industry). Lack of public funding has pushed many farmers to rely on private crop advisors, who don't always share conservation opportunities (like cover crops, reduced tillage, and nutrient management) with farmers (especially as tied to programs involving lots of paperwork). They found it was critical to improve active communication & trust at all levels (especially about funding available).  Conservation was constrained by funding, and potentially by the shift of crop advisors to often be less comprehensive and represent a single company. The authors emphasize the need to integrate social science like this from the very beginning of projects.


REFERENCES:
Brancalion, P. H. S., Niamir, A., Broadbent, E., Crouzeilles, R., Barros, F. S. M., Almeyda Zambrano, A. M., … Chazdon, R. L. (2019). Global restoration opportunities in tropical rainforest landscapes. Science Advances, 5(7), eaav3223. https://doi.org/10.1126/sciadv.aav3223

Chaplin-Kramer, R., Sharp, R. P., Weil, C., Bennett, E. M., Pascual, U., Arkema, K. K., … Daily, G. C. (2019). Global modeling of nature’s contributions to people. Science, 366(6462), 255–258. https://doi.org/10.1126/SCIENCE.AAW3372

Fahrig, L. (2017). Ecological Responses to Habitat Fragmentation Per Se. Annual Review of Ecology, Evolution, and Systematics, 48(1), annurev-ecolsys-110316-022612. https://doi.org/10.1146/annurev-ecolsys-110316-022612

Fahrig, L., Arroyo-Rodríguez, V., Bennett, J. R., Boucher-Lalonde, V., Cazetta, E., Currie, D. J., … Watling, J. I. (2019). Is habitat fragmentation bad for biodiversity? Biological Conservation, 230(October 2018), 179–186. https://doi.org/10.1016/j.biocon.2018.12.026

Hamel, P., Bremer, L. L., Ponette-González, A. G., Acosta, E., Fisher, J. R. B., Steele, B., … Brauman, K. A. (2020). The value of hydrologic information for watershed management programs: The case of Camboriú, Brazil. Science of The Total Environment, 135871. https://doi.org/10.1016/j.scitotenv.2019.135871

Johnson, K. A., Wing, O. E. J., Bates, P. D., Fargione, J., Kroeger, T., Larson, W. D., … Smith, A. M. (2019). A benefit–cost analysis of floodplain land acquisition for US flood damage reduction. Nature Sustainability. https://doi.org/10.1038/s41893-019-0437-5

Jones, P. F., Jakes, A. F., Telander, A. C., Sawyer, H., Martin, B. H., & Hebblewhite, M. (2019). Fences reduce habitat for a partially migratory ungulate in the Northern Sagebrush Steppe. Ecosphere, 10(7). https://doi.org/10.1002/ecs2.2782

Samanta, A., Eanes, F. R., Wickerham, B., Fales, M., Bulla, B. R., & Prokopy, L. S. (2019). Communication, Partnerships, and the Role of Social Science: Conservation Delivery in a Brave New World. Society & Natural Resources, 0(0), 1–13. https://doi.org/10.1080/08941920.2019.1695990

Sippel, S., Meinshausen, N., Fischer, E. M., Székely, E., & Knutti, R. (2020). Climate change now detectable from any single day of weather at global scale. Nature Climate Change, 10(1), 35–41. https://doi.org/10.1038/s41558-019-0666-7

Sincerely,

Jon

p.s. 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/

Monday, January 6, 2020

Can science boost credibility even if it isn't used?

Hamel et al. 2020 ("The value of hydrologic information for watershed management programs: The case of Camboriú, Brazil") looked at how scientific information was perceived and used in decision making for a water fund in Brazil (where a water treatment company pays for upstream conservation to reduce the costs of treating the water).

Through interviews, we determined that the hydrological modeling and monitoring data that we provided was NOT used in designing and implementing the water fund. But counter-intuitively, having done the analysis using complex models and high-resolution data was seen as important for the water fund to be seen as scientifically credible.

So ironically, even though the credible models were not actually used, their existence helped build support for the overall water fund. Despite this, as long as monitoring data was used to calibrate and validate the model, a simpler model (InVEST, as opposed to SWAT) and coarser data resolution (30m, as opposed to 1m) would have met the information needs of the users. We should have had more frank discussions up front with the ultimate users of the information to produce a model seen as credible and actually used, while avoiding over-investment in model complexity that wasn't needed.

You can read the full article here: https://www.sciencedirect.com/science/article/pii/S0048969719358668

Reference:
Hamel, P., Bremer, L. L., Ponette-González, A. G., Acosta, E., Fisher, J. R. B., Steele, B., … Brauman, K. A. (2020). The value of hydrologic information for watershed management programs: The case of Camboriú, Brazil. Science of The Total Environment, 135871. https://doi.org/10.1016/j.scitotenv.2019.135871

Thursday, January 2, 2020

January 2020 science journal article summary: best of 2019

Frozen roots

Happy new year!

I’ve decided once again to kick the new year off by listing my favorite 15 articles that I reviewed last year. I picked them for a mix of importance and being interesting, plus my favorite two publications that I contributed to (Bradford et al. 2019, Fisher & Kareiva 2019). If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

I also have gotten a great response from a webinar I hosted in December on how scientists can improve the impact of their research! If you weren't one of the almost 1,000 registrants, you can watch the webinar here: https://www.openchannels.org/webinars/2019/improving-your-impact-guidelines-doing-science-influences-policy-and-management It's about 23 minutes of presentation followed by lots of Q&A and discussion, and you can also download the full paper the talk is based on from http://bit.ly/strongerscience 

Anderson et al. 2019 argues that while investing in natural climate solutions (aka NCS, e.g. trees) is important to mitigate climate change, cuts to emissions from energy and industry are also urgent and imperative. As they put it, it's not "either/or" but "yes, and." Their key point is that while NCS offer many benefits, delaying emissions reductions from energy and industry by even a few years can add up to more than offset the reductions from NCS. They close by calling for conservationists to ensure that NCS mitigation is optimized, while also amplifying the need to work on complementary solutions to reduce anthropogenic emissions at their source.

Bradford et al. 2019 is an opinion piece on soil carbon. The opening two lines sum it up well: "Soil-based initiatives to mitigate climate change and restore soil fertility both rely on rebuilding soil organic carbon. Controversy about the role soils might play in climate change mitigation is, consequently, undermining actions to restore soils for improved agricultural and environmental outcomes." In other words, while scientists disagree a lot about whether boosting soil carbon is useful for climate mitigation, we all pretty much agree it's important for fertile and productive agricultural lands. Read a bit more at http://sciencejon.blogspot.com/2019/11/soil-carbon-what-is-it-good-for.html  or just read the paper (it's only 1,800 words).

Burivalova et al. 2019 is a literature review of how effective four strategies were in delivering environmental, social, and economic outcomes. They looked at creating protected areas (PAs), forest certification and reduced impact logging (RIL), payment for ecosystem services, and community forest management. The results are varied and complex but Figure 2 summarizes them very well - no strategies always succeed, but all sometimes succeed (and note the caveat that each square is not equivalent). PAs performed well environmentally (after certification & RIL), but very poorly socially and economically. The authors conclude that there are surprising gaps in the literature on monitoring the efficacy of conservation strategies, and that before implementation local evidence should be examined to minimize the chance of failure or even having a strategy backfire.

Catalano et al. 2018 argues that conservation would do well to learn how to deal with failure from other disciplines like medicine, business, and aviation. Specifically, we need to recognize how much we can learn from failure (sometimes more than success), rather than fearing it and avoiding tough measures as a result. They cover how we learn from failure, why it's hard to constructively engage with it, how understanding cognitive biases can help (see Table 1 for a great list to consider), and the role of leaders in supporting efforts to identify and learn from failure. The example of "no rank" military aviation debriefs is interesting - they promote a culture with sharing useful feedack at its core. My main take-away is that dealing with failure is not only key, but it's hard and requires careful thought to do well.

The U.N.'s Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) released a summary of a major report in May describing global biodiversity loss and extinctions (Diaz et al. 2019). The short version is "nature is in trouble, and so are we as a result." The most reported estimate is that about 1 million species face extinction (many within decades) unless we act to prevent that. I'd recommend looking at the policy summary and at least reading the bold headlines to get a bit more of the key findings. A few others worth highlighting include: declines in crop and livestock diversity is undermining agricultural resilience, drivers of change in nature (e.g. land use, direct exploitation, climate change, pollution, and invasives) are accelerating, goals like the Aichi Biodiversity Target and the 2030 Agenda for Sustainable Development cannot be met without major transformative changes (changes which are possible, albeit challenging), the parts of the world where declining nature is expected to hit people the hardest tend to be poor and/or indigenous communities, international cooperation to build a more sustainable global economy will be key to solve this problem, addressing the sustainability of food will also be important, and land-based climate solutions (e.g. bioenergy plantations and afforestation) have some tradeoffs. Many of these are obvious; the summaries under each headline often include useful detail, but there's too much to summarize at this level. So skim through and dive into the topics that pique your interest. Download the whole report from https://ipbes.net/global-assessment

My long-overdue book chapter "Using environmental metrics to promote sustainability and resilience in agriculture" (Fisher & Kareiva 2019) came out in "Agricultural Resilience: Perspectives from Ecology and Economics" from Cambridge University Press: https://www.cambridge.org/gb/academic/subjects/life-sciences/ecology-and-conservation/agricultural-resilience-perspectives-ecology-and-economics?format=PB Unfortunately I wrote it when I knew far less about agriculture, but it has some useful content. The section "Food labels and sustainability" is still unique as far as I know in providing a concise (2 page) summary of research around food labels and consumer preferences around sustainability (although there are more comprehensive resources, e.g. "The Green Bundle" by Magali Delmas and David Colgan). The corporate sustainability information is badly dated but a decent primer for folks new to the field. Anyway, you can read my chapter here if interested: http://fish.freeshell.org/publications/FisherKareiva_CUP_2019_preformatted.pdf or buy the book from the link above.

Grill et al. 2019 estimates only about a third of the world's longest rivers (<1,000 km) are freely flowing (defined here with a new metric that means neither dammed, nor significantly impacted by water consumption or infrastructure in riparian areas and floodplains). Those long free rivers are mostly in remote parts of the Amazon, Arctic, and Congo. On the other hand, shorter river reaches are doing better: 56% of long rivers (500-1000km) are freely flowing, rising to 80% and 97% for medium (100-500km) and short (10-100km) rivers respectively. However, since they rely on global dam databases, they caution that they likely overestimate freely flowing rivers due to missing data on small dams. The figures (and table 1) have great details on how well connected each river reach is, what limits connectivity most (96% one of the impacts of dams: fragmentation, flow regulation, and sediment trapping), and connectivity broken down by river length.

Kennedy et al. 2019 calculates how modified by human activities land around the world is. While only 5% of land area was 'unmodified', most of the world was 'moderately modified.' The authors argue that ecoregions with moderate modification may be good candidates for high priority conservation action, because they tend to have some relatively intact lands near to highly modified lands (which thus may pose a threat in the near future). In particular, the tropical and subtropical dry broadleaf forests biome (mostly in Mexico, India, Argentina, & SE Asia) was found to be the most threatened (high conversion relative to protection). While they didn't include all threats (e.g. logging, invasive species, climate change, and more) these data can be used to evaluate the suitability of lands for protection. You can explore the findings and maps at http://gdra-tnc.org/current/ and you can download the data from http://s3.amazonaws.com/DevByDesign-Web/Apps/gHM/index.html

Li et al. 2015 compares the net impact of different kinds of forests on local weather, considering albedo and evapotranspiration. Their key finding is that "tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually; and boreal forests have strong warming in winter and moderate cooling in summer with net warming annually." This means that the net climatic effect (accounting for carbon sequestration as well as local weather) of tropical forests (and to a lesser extent, temperate forests) is stronger than indicated by carbon alone, while for boreal forests the carbon benefit is significantly offset.

Minx et al. 2018 is an overview from a 3-part series on negative emissions (which they define as reforestation, soil carbon, biochar, BECCS, DACCS, enhanced weathering & ocean alkalinization, and ocean fertilization). Table 2 summarizes potential impact and costs from various studies, and Fig 6 has a great visual synthesis of these data. They find afforestation, reforestation, and soil carbon as ready for large-scale deployment (albeit reversible), and all but ocean fertilization as having potential to deliver benefits by 2050. There are lots of other good insights here and it's worth reading.

Two new lidar satellites were launched recently: ICESat-2 launched in Sep 2018 and GEDI in Dec (initial GEDI data should be released in June, ICESat-2 hasn't announced a date yet). While GEDI is more focused on measuring forest canopy height, ICESat-2 is also mapping vegetation (in addition to ice sheets, clouds, land surface, and more). GEDI will focus on middle latitudes, and ICESat-2 on the poles. Having these data available globally will be a big deal, especially for estimating forest carbon. For more on ICESat-2, Neuenschwander and Pitts 2019 has details on one of the planned data products (ATL08) which maps both ground surface and tree canopies. It's a dense paper, but Figures 4 & 8 are useful to get a sense of the output (they used simulated data), and the discussion has several useful details. The raw data is grouped into 100m cells to have enough photons per cell, but another data product (ATL03) maps each photon individually and can be used to investigate patterns within each 100m cell. Note that tree canopy height is consistently underestimated by ATL08.

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.

Pohl et al. 2017 is a cool but unusual science paper. The authors provide clear instructions in 10 steps for researchers to improve their impact (similar to the concepts in Enquist et al. 2017 but aimed at implementation). Table 1 has a great summary of the process - at a high level they recommend matching research questions to knowledge needed to inform action, thinking about who to involve (e.g. stakeholders) throughout the research process, and reflecting on lessons learned. The authors have walked a variety of researchers through these 10 steps in a single day. Steps 5-9 provide helpful tips on how to identify a body of stakeholders, and figure out how to break them down into who to co-produce knowledge with, who to consult with, and who to simply inform. It seems like a great framework to get scientists started, although it's a bit ironic to have scientists think on their own about how to better incorporate input and perspectives from stakeholders.

Sanchez-Bayo & Wyckhuys 2019 looks across 73 studies of insect decline from cross the world, and look at the drivers and other commonalities. A key limit of the paper is that they excluded any study that did NOT show a chance in abundance or diversity, so its utility is limited to explaining declines where they have happened (see section 4.1) as opposed to quantifying how insect populations are changing overall. The take-away is that habitat loss seems to be the primary driver (~50% of declines), followed by 'pollution' (~26%, mostly pesticides and fertilizer), then disease and invasive species (18%) and climate change (7%). That means a sole focus on pesticides will miss key drivers of the problem. Figure 3 has a breakdown by taxonomic order, highlighting that dung beetles are in real trouble.

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


REFERENCES:
Anderson, C. M., DeFries, R. S., Litterman, R., Matson, P. A., Nepstad, D. C., Pacala, S., … Field, C. B. (2019). Natural climate solutions are not enough. Science, 363(6430), 933–934. https://doi.org/10.1126/science.aaw2741    

Bradford MA, Carey CJ, Atwood L, Bossio D, Fenichel EP, Gennet S, Fargione J, Fisher JRB, Fuller E, Kane DA, Lehmann J, Oldfield EE, Ordway EM, Rudek J, Sanderman J, Wood SA. 2019. Soil carbon science for policy and practice. Nature Sustainability. http://doi.org/10.1038/s41893-019-0431-y

Burivalova, Z., Allnutt, T., Rademacher, D., Schlemm, A., Wilcove, D. S., & Butler, R. A. (2019). What works in tropical forest conservation, and what does not: Effectiveness of four strategies in terms of environmental, social, and economic outcomes. Conservation Science and Practice, in press(March), 1–15. https://doi.org/10.1111/csp2.28

Catalano AS, Redford K, Margoluis R, Knight AT. 2018. Black swans, cognition, and the power of learning from failure. Conservation Biology 32: 584–596. https://onlinelibrary.wiley.com/doi/abs/10.1111/cobi.13045

Díaz, S., Settele, J., Brondízio, E., Ngo, H. T., Guèze, M., Agard, J., … Zayes, C. (2019). Summary for policymakers of the global assessment report on biodiversity and ecosystem services-unedited advance version. Retrieved from https://www.ipbes.net/news/ipbes-global-assessment-summary-policymakers-pdf and https://ipbes.net/global-assessment

Fisher, J.R.B. and Kareiva, P. 2019. Using environmental metrics to promote sustainability and resilience in agriculture. In Gardner et al. (Eds), Agricultural Resilience: Perspectives from Ecology and Economics. Cambridge University Press. https://www.cambridge.org/us/academic/subjects/life-sciences/ecology-and-conservation/agricultural-resilience-perspectives-ecology-and-economics?format=PB

Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F., … Zarfl, C. (2019). Mapping the world’s free-flowing rivers. Nature, 569(7755), 215–221. https://doi.org/10.1038/s41586-019-1111-9

Kennedy, C. M., Oakleaf, J. R., Theobald, D. M., Baruch-Mordo, S., & Kiesecker, J. (2019). Managing the Middle: A Shift in Conservation Priorities based on the Global Human Modification Gradient. Global Change Biology, (June 2018), 1–17. https://doi.org/10.1111/gcb.14549
Li Y, Zhao M, Motesharrei S, Mu Q, Kalnay E, Li S. 2015. Local cooling and warming effects of forests based on satellite observations. Nature Communications 6: 1–8. https://www.nature.com/articles/ncomms7603

Minx JC, Lamb WF, Callaghan MW, Fuss S, Hilaire J, Creutzig F, Amann T, Beringer T, De Oliveira Garcia W, Hartmann J, Khanna T, Lenzi D, Luderer G, Nemet GF, Rogelj J, Smith P, Vicente Vicente JL, Wilcox J, Del Mar Zamora Dominguez M. 2018. Negative emissions - Part 1: Research landscape and synthesis. Environmental Research Letters 13. https://iopscience.iop.org/article/10.1088/1748-9326/aabf9b/meta

Neuenschwander, A., & Pitts, K. (2019). The ATL08 land and vegetation product for the ICESat-2 Mission. Remote Sensing of Environment, 221 (April 2018), 247–259. https://doi.org/10.1016/j.rse.2018.11.005

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(1), 15–32. https://doi.org/10.5194/soil-5-15-2019

Pohl, C., Krütli, P., & Stauffacher, M. (2017). Ten reflective steps for rendering research societally relevant. GAIA, 26(1), 43–51. https://doi.org/10.14512/gaia.26.1.10

Sánchez-Bayo, F., & Wyckhuys, K. A. G. (2019). Worldwide decline of the entomofauna: A review of its drivers. Biological Conservation, 232(January), 8–27. https://doi.org/10.1016/j.biocon.2019.01.020

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

Monday, December 2, 2019

December 2019 science journal article summary

Pig in mud at poplar springs 2018 open house
Greetings,

This month I've just got a couple articles each on soil and learning from failure, plus one on social and environmental synergies and trade-offs. If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

Also, as a reminder, I'm hosting a webinar on December 3 (1p EST) with recommendations on how scientists may be able to achieve more real world impact via their research. You can learn more and register here: https://zoom.us/webinar/register/WN_Q78ubqH9TL6tkmLQCRyAsw and read the draft paper the talk is based on at http://bit.ly/strongerscience

SOIL:
Our paper opining on soil carbon (Bradford et al. 2019) is out! The opening two lines sum it up well: "Soil-based initiatives to mitigate climate change and restore soil fertility both rely on rebuilding soil organic carbon. Controversy about the role soils might play in climate change mitigation is, consequently, undermining actions to restore soils for improved agricultural and environmental outcomes." In other words, while scientists disagree a lot about whether boosting soil carbon is useful for climate mitigation, we all pretty much agree it's important for fertile and productive agricultural lands. Read a bit more at http://sciencejon.blogspot.com/2019/11/soil-carbon-what-is-it-good-for.html or just read the paper (it's only 1,800 words).

Lugato et al. 2018 uses daycent to model the net GHG impact of building soil carbon in farms via cover crops, reduced tillage, and keeping crop residues. They found a lot of variation across sites, but that overall reducing tillage and crop residue retention offered modest but long term (>80 years) net GHG benefits without impacting crop yield much. N-fixing cover crops led to stronger C sequestration and net GHG reductions over the first 20 years, but after 40 years it switched to being a GHG source (due to N2O) that strengthened over time (albeit with a small crop yield boost). If fertilization wasn't reduced to account for the new N from the cover crop, it would be a stronger GHG source much sooner. They also didn't model non-N-fixing cover crops like rye.


ORGANIZATIONAL LEARNING / FAILURE:
Catalano et al. 2018 argues that conservation would do well to learn how to deal with failure from other disciplines like medicine, business, and aviation. Specifically, we need to recognize how much we can learn from failure (sometimes more than success), rather than fearing it and avoiding tough measures as a result. They cover how we learn from failure, why it's hard to constructively engage with it, how understanding cognitive biases can help (see Table 1 for a great list to consider), and the role of leaders in supporting efforts to identify and learn from failure. The example of "no rank" military aviation debriefs is interesting - they promote a culture with sharing useful feedack at its core. My main take-away is that dealing with failure is not only key, but it's hard and requires careful thought to do well.

Catalano et al. 2019 is an analysis of 59 peer-reviewed articles discussing reported conservation failure (Table 2 has a great list of synonyms and euphemisms for failure). Most articles did use the term failure, and almost half did so in the abstract. See Table 3 for an interesting typology of causes of failure (including people, action, information, funding, and economic and political) and how common each was, and Table 4 for example text of each kind. Overall they found reporting failure in conservation is rare (~1/4 as often as reporting success), it's typically not framed as useful for learning, and 'people' are the most common cause of failure (e.g. especially stakeholder relationships, but also bad past experiences, fear, etc.). They also call for authors to report failure in a way that makes it easy for others to learn from their mistakes.


PEOPLE AND NATURE:
Gill et al. 2019 looks at 75 studies across 4 kinds of marine conservation work to evaluate social and environmental synergies and tradeoffs (as well as equity). Specifically: marine protected areas (MPAs - representing the majority of studies considered), community-based MPAs, environmental certification, and community-based management (CBM). They found diverse impacts, but with very few rigorous studies designed to show causality. But there was potential for both positive and negative cascading effects depending on access to resources (especially for fishers). Fig 6 has an interesting breakdown of how many studies covered each subtopic, and provides some potential categories of trade-offs to think about.


REFERENCES:
Bradford MA, Carey CJ, Atwood L, Bossio D, Fenichel EP, Gennet S, Fargione J, Fisher JRB, Fuller E, Kane DA, Lehmann J, Oldfield EE, Ordway EM, Rudek J, Sanderman J, Wood SA. 2019. Soil carbon science for policy and practice. Nature Sustainability .

Catalano AS, Redford K, Margoluis R, Knight AT. 2018. Black swans, cognition, and the power of learning from failure. Conservation Biology 32: 584–596.

Catalano AS, Lyons-White J, Mills MM, Knight AT. 2019. Learning from published project failures in conservation. Biological Conservation 238: 108223.

Gill DA, Cheng SH, Glew L, Aigner E, Bennett NJ, Mascia MB. 2019. Social Synergies, Tradeoffs, and Equity in Marine Conservation Impacts. Annual Review of Environment and Resources 44: 347–372.

Lugato E, Leip A, Jones A. 2018. Mitigation potential of soil carbon management overestimated by neglecting N2O emissions. Nature Climate Change 8: 219–223.


Sincerely,

Jon

p.s. 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/