Tuesday, January 3, 2023

Best of 2022 science summary

A man (Jon Fisher) carrying a large Christmas tree at an angle using a wheeled dolly. He is wearing a green Swiss Alpine hat and smiling.

Happy New Year!

As usual, I'm resending summaries of my favorite 15 articles from 2022, but in case you missed any. This year I tried to group them by topic and subtopic rather than just alphabetical, but some could fit in multiple categories so apologies if it's confusing!

Hamilton et al. 2022 is the latest analysis from NatureServe on biodiversity in the U.S., and potential priorities for new protection. They looked at habitat for 2,216 imperiled species (G1 or G2 globally, or Threatened or Endangered nationally) across the U.S., including often overlooked species like plants and bugs. There are several interesting methodological advances here (relatively fine 1-km pixels, inclusion of overlooked species, using both range maps and habitat suitability models and showing how that changes results in Fig 4, etc.), but I think most readers will want to focus on implications for new protections and management of existing protected areas. Fig 2 shows the most important areas to protect. They use protection-weighted range-size rarity, which is a kind of rarity-weighted richness focusing on places with a) relatively high # of species that b) have relatively little habitat left nationally. Table 2 has a nice summary of how many species have the majority of their habitat managed by different groups (federal agencies, state & local, private), showing there is a lot of potential for management on existing public lands (since 43% of imperiled species have most of their habitat on public lands). It's worth reading the whole thing, but if short on time I recommend the NY Times article about this (https://www.nytimes.com/interactive/2022/03/03/climate/biodiversity-map.htm) and especially the interactive maps of their data online at https://livingatlas.arcgis.com/en/browse/?q=mobi#d=2&q=mobi%20owner%3ANatureServe&srt=name
Saran et al. 2022 has a good overview of biodiversity information portals, 16 global (Table 1) and 5 country-specific (from Australia, Canada, India, and the U.S., Table 2). It's a great complement to Nicholson et al. 2021 (an overview of ecosystem indicators) by providing actual data sources and some info about what each portal includes. The paper certainly isn't "comprehensive" as the title advertises, but it's a great start and I learned about some new useful resources by reading it.

Climate adaptation
Dreiss et al. 2022 identifies priority conservation locations within the contiguous US to support climate adaptation (via refugia and corridors). Fig 4c shows which climate refugia and corridors are unprotected (in gray) or underprotected (GAP 3 in orange). The bottom two rows in Table 3 shows that the best places for climate adaptation mostly don't overlap with the best places for biodiversity or carbon (~20-25% do). This means that focusing solely on biodiversity or carbon hotspots is likely to miss critical refugia and corridors to help ensure resilience to climate change.
Climate mitigation:
Noon et al. 2022 is a fantastic resource mapping global priority habitats for conservation to protect and/or manage to slow climate change. They focus on "irrecoverable carbon" - meaning carbon that will take 30+ years to recover after it is lost due to conversion or degradation. Fig 1 has a global map of irrecoverable carbon with a few hotspots highlighted (or use this web map which has slightly different symbology https://irrecoverable.resilienceatlas.org/map). But more useful is Fig 2 which splits out the carbon by how it's threatened (by land conversion, climate change, both, or neither) to identify where protection vs. management makes sense. Note that in Fig 2 darker colors mean more carbon within each of the four risks, but they are not consistent across the four risks (to see the highest total carbon you still need Fig 1). Fig 3 highlights how uneven irrecoverable carbon in, 50% of it is in just 3% of global land area! If you work on carbon in nature, read the whole paper. Many thanks to the authors who kindly answered my questions and sent me their data so I could make my own maps!
Sullivan-Stack et al. 2022 is a great summary of marine protected areas (MPAs) in the U.S., and flags that achieving 30% U.S. ocean protection by 2030 is not on track to provide sufficient benefit to marine ecosystems. The key finding that stood out to me was the need for improving both geographic representation and efficacy / strength of protection (as well as climate resilience and equity). U.S. oceans are 26% protected overall (25% fully or highly protected), but 96% of that is in the central Pacific ocean. Excluding that region, only 2% has any protection (and only 22% of that 2% is fully or highly protected). See Table 3 for a summary of how much of each region is protected and at what level (Figure 1 has a map but it's not split by protection strength). Alaska has the lowest % protection of any kind (0.7%) while OR & WA have the weakest protection (4.2% of ocean is protected, but that's all minimal protection). Skip to section 4 for their recommendations: create more effective MPAs (via new ones and strengthening existing ones), improve representation of different marine regions & species & habitats in well-connected MPAs, improve equity & access, go beyond tracking % coverage and include impact assessments, make MPAs durable and climate resilient, coordinate state MPAs, reinstate and empower the MPA Federal Advisory Committee, strengthen & fund the NOAA MPA Center, and update the U.S. National Ocean Policy for holistic ocean planning and management.

Multiple goals
Dreiss & Malcom 2022 is an analysis of U.S. priorities for protection under 30x30, considering hotspots of biodiversity and carbon, current protection (Fig 2), and threats. The two threats are risk of conversion (to non-habitat by 2050) and climate vulnerability (need for habitat / species to migrate elsewhere to survive, expressed in km/yr). They have two sets of hotspots, one with the top 10% of biodiversity (they calculated both imperiled species richness, and imperiled species range-size-rarity which captures how much habitat rare spp. have left), and one with the top 10% of carbon pools (not actual GHG mitigation potential, as it omits deep carbon like peat, other GHGs, and the albedo effect). Fig 3 has maps of their main results, but they're easier to see and explore in the interactive map at https://arcg.is/0SjGLK. Fig 4 highlights high conversion risk (>50%) and climate vulnerability for hotspots (top 10%) of biodiversity and carbon (4a = conversion & richness, 4b = conversion & carbon, 4c = climate vuln. & richness, 4d = climate vuln. & carbon). Upgrading all existing less strict protected areas (GAP 3) would achieve ~30% protection, but that would miss 80% of biodiversity hotspots (which are on private land). Similarly, 21% of unprotected biodiversity hotspots have at least a 50% chance of being converted by 2050. The authors didn't include political, social, or economic considerations, but there are still a lot of useful data in here.
As conservation organizations try to work towards multiple goals, Vijay et al. 2022 asks whether we can protect places that efficiently advance multiple goals at once, or if we have to pick between places good for one goal but that perform poorly for others. We (I’m an author) looked at opportunities to advance five benefits by protecting land in the contiguous United States: vertebrate species richness, threatened vertebrate species richness, carbon storage, area protected, and recreational usage. Specifically we looked at Return On Investment (ROI) meaning the benefit score compared to the cost of the land (as a proxy for difficulty of protecting it). The results are a bit complicated: this paper focused only on unprotected habitat which is predicted to be converted by 2100, and with that framing the four environmental benefits were both highly correlated overall (r 0.89-0.99) and had a lot of the "top sites" in common (the highest scoring places for one benefit often had a top score for another benefit, 32-79% of the time). Recreation had less in common with environmental benefits (r 0.5-0.52, only 7-13% of the top sites were also a top site for another benefit). That still shows a lot of opportunity for win-wins across the nation! However, if you DON'T constrain conservation to places where land use is projected to change by 2100, win-wins are harder to find (as shown in the Supplementary Information). Species richness and area were the most compatible with a high r of 0.58 and 24% of top sites in common, and area and recreation were the least aligned, with an r of -0.65 and no top sites in common. There's a lot of interesting stuff in the paper (including comparing how three hypothetical policy scenarios score on each benefit), and I've written a slightly longer summary here: https://www.linkedin.com/posts/sciencejon_conservation-science-goalsetting-activity-6948122284528197632-OH0S/

Sze et al. 2021 compares deforestation and degradation on protected Indigenous lands, unprotected Indigenous lands, protected non-Indigenous lands, and unprotected non-Indigenous lands. Their abstract slightly misrepresents their results, which found that Indigenous lands in the tropics typically provide modest protection against deforestation and degradation, roughly similar to formal protected areas (whether Indigenous or not). The results vary by geography; in Africa unprotected Indigenous lands do even better than protected areas by most measures, but in the Americas Indigenous lands (whether protected or not) fared worse than non-Indigenous protected areas, although still better than non-Indigenous unprotected areas. In some other cases Indigenous lands seem to offer little to no improvement over unprotected non-Indigenous lands. Just comparing non-Indigenous protected areas to Indigenous protected areas, in a slight majority of cases deforestation and degradation are higher in the IPAs (but with some exceptions being similar, and degradation in Asia-Pacific being lower in IPAs); this is surprising given the other findings and makes me think that their matching process (to control for confounding variables) didn't catch everything. Another way to look at their results is that in ~90% of cases they evaluated (the 36 dark lines in Fig 2, considering both geography and data source), both protected areas and Indigenous lands (whether protected or not) experience less deforestation and degradation than unprotected non-Indigenous areas). In the remaining ~10% of cases unprotected and non-Indigenous areas have either similar levels of deforestation and degradation to protected and/or Indigenous lands, or less deforestation and degradation. Overall, the main take-away on efficacy of Indigenous lands for protection is “promising but it depends.” Their results really depend on their matching process (since without it deforestation and degradation is actually lowest in non-protected and non-Indigenous areas in a slight majority of cases). It looks like the matching should correct for confounding factors like Indigenous areas tending to be located farther from development and on lower-value lands. Most of the differences they find are pretty small. So I end up concluding that in this paper Indigenous lands are very roughly on par with protected areas, but that it’s not definitive and depends on geography.

You're probably familiar with the IUCN's Red List of Threatened Species - which ranks how at risk species around the world are. Comer et al. 2022 is an analysis for the Red List of ECOSYSTEMS for North America - looking at the risk of ecological collapse for 655 terrestrial ecosystems considering: current extent, how much historic extent has been lost, degradation from historic fire regime, and disruption of biotic processes (focused on invasive species and landscape fragmentation). They found 1/3 of ecosystems were threatened, and Fig 2 shows which types of ecosystems were the most threatened (like Mediterranean Scrub & Grassland, which had the highest % of extent that was threatened, and Tropical Montane Grassland & Shrubland, which had the highest % Critically Endangered). Fig 1 has a great pair of maps showing both current and historic extent of all assessed ecosystems (colored by threat level). There is also an excellent discussion of the challenges and limitations in doing an analysis like this (section 4.2). Despite these limitations, this provides a useful complement to species-focused prioritizations (like range-size rarity).

Nicholson et al. 2021 is chock full of useful diagrams and lists for ecosystem indicators. They have a number of recommendations for setting ecosystem goals (which have milestones, targets, and indicators) for a global biodiversity framework, but which can be relevant to other efforts (like 30x30). At a high level they flag the need to track not only total ecosystem/habitat area (or extent), but also changes in ecosystem integrity (including the risk of ecosystem collapse - see Box 2 for definitions). Fig 2 is a nice visual summary of how different types of targets can collectively capture different threats and ecosystem attributes that need to be addressed for long term ecosystem health. Fig 3 is a super helpful review of many different environmental indices / metrics, and what aspects of ecosystems they include and omit. Spend some time with that one - even learning about all of the indices was very helpful for me. They close with 6 recommendations for picking indicators: we need a set of them (no single one suffices), they need to reflect goals (not actions), relevance to the goal is at least as important as data availability, we need more testing and validation of indicators, we need stronger connections between global indicators and national or local policies, and we need new indicators to provide early warning of ecosystem collapse.

Fire management & Race
Anderson et al. 2020 found that rich white communities who had a fire nearby tend to get additional prescribed fire (even when not needed). This is partly due to their ability to self-advocate at relevant planning meetings. It raises equity and social justice concerns about how we could instead base fire management on factors like social and/or ecological vulnerability. As context, here is a map showing how wildfire risk varies across the U.S.: https://www.nytimes.com/interactive/2022/05/16/climate/wildfire-risk-map-properties.html

Gender and Science
James et al. 2022 is an analysis of how gender relates to scientific publication at The Nature Conservancy (TNC). We (I’m an author) analyzed almost 3,000 peer-reviewed scientific publications from 1968 to 2019 with at least one TNC author. Roughly 1/3 of the TNC authors and authorships (# authors * # papers) were women, even though 45% of conservation and science staff are women. Most authorships were in the U.S. - 85% overall and 90% for women. This means men (especially men in the United States) are publishing at a significantly higher rate than women. We close with several recommendations to help shrink this gap. Some are aimed at individual scientists (e.g., self-education on bias and systemic barriers, asking men to collaborate more with women as male-led papers have far fewer women co-authors than female-led papers, and asking lead authors to be more inclusive in determining whose contributions merit being listed as an author), and others are aimed at organizations (e.g., providing more resources and support for women who wish to publish, especially for women who don't speak English as a first language). I learned a ton from both the data and my co-authors on this one, and we have another 1-2 papers on the subject coming which will get into the results of a survey the lead author did to get deeper into the experience of how gender impacts not only publication but perceptions of influence and career advancement. Note that our available data listed everyone's gender as male, female, or unknown - apologies to those who we misgendered or otherwise failed to reflect their lived experience with a relatively simple binary analysis (especially as gender diverse people appear to be even more underrepresented in science publications).
You can read blogs about the article at https://www.nature.org/en-us/newsroom/published-science-gender-gap/ and https://blog.nature.org/science/science-brief/conservation-science-publishing-has-a-gender-problem/

Higgins et al. 2021 offers a very helpful framework for how to effectively conserve freshwater ecosystems. They argue that since freshwater species are declining faster than terrestrial species, and effective durable freshwater conservation is typically harder to get right, we need more thoughtful design of freshwater protection and management. Their framework begins with key questions (about things like what you value, key ecological attributes [KEAs] to conserve, threats to ecosystems, and protection options), which is summarized in Figure 1. Table 1 is extremely useful: it outlines 5 key ecological attributes that freshwater systems need: 1) hydrologic regime / healthy flow, 2) connectivity , 3) water quality (nutrients, sediment, toxins, etc.), 4) habitat (riparian, in-stream, other wetlands), 5) species (diversity, abundance, invasives). Table 1 also lists threats, Table 2 has conservation options, and Table 3 has helpful and relatively simple examples to get you started. Doing this work is hard! But I found this article to be a great challenge to keep thinking beyond protecting the land around freshwater ecosystems, and planning for what they need over the long-term. The lead author (Jonathan Higgins) passed away last year, you can read more about his life at https://jvhiggins.com/

Halpern et al. 2022 is the latest paper to try and compare the global environmental footprint of almost all foods (both aquatic and terrestrial), using greenhouse gases (GHGs but excluding land use change), "blue" water consumption (from irrigation), nutrient pollution (N&P, excluding crop N fixing), and land use. Note that blue water consumption excludes rainfall, and focuses on evaporation & transpiration as opposed to "water use" (the amount pumped out) much of which returns to surface and ground water. This lets us compare the impact of different foods, look at which foods have the most total impact (and thus offer the most opportunity to improve via changes in practice or biology), and see which countries have the most environmental impact from food (India, China, the U.S., Brazil, and Pakistan - see Figs 2, 3, and especially 4). Spend some time with Fig 4, it's dense and interesting. For example, you can see that India has slightly more total impact than China, but produces substantially less food by all 3 metrics (calories, protein, and mass). Most of the data here are similar to what we've seen before, but still interesting (e.g., U.S. soy is 2.4 times more efficient than Indian soy). Reporting "cumulative" impacts can be confusing - wheat and rice have similar total impact in Fig 5, but Fig 6 shows that rice is far more inefficient per tons of protein produced). Fig 5 and 6 would be useful in looking at which crops and livestock species to focus on improved genetics or practices to have the most impact. But if you want to know "what should I eat" this paper makes it really hard to find that (Fig 6 is closest, or look at Supplementary Data 3 for country-specific "total environmental pressure" data using the food key from Table S6). So for example they find goats have a higher impact than cows, and in the US soy is the most environmentally efficient source of protein while sugar beets are the most environmentally efficient source of calories.

Richardson et al. 2022 estimates the potential climate mitigation benefits of rewetting drained peatlands (specifically pocosin - a bog found in the SE US dominated by trees and/or shrubs). They measured water table depth, soil characteristics, dissolved organic carbon, and emissions of CO2 & methand & nitrous oxide at 5 sites (3 drained, 1 restored, 1 natural). The drained peatlands emitted a net of 21.2 t CO2e / ha (Table 2). They conducted additional detailed measurements on the drained peatlands, and combined the data into a model to predict how water table would impact emissions. Methane and nitrous oxide were excluded since CO2 was responsible for 98% of CO2e (Fig 3). Validation found the model to be conservative and w/in 18% of measurements out of the training sample. The pocosin always emit more carbon than they absorb in fall and winter, but re-wetting peat resulted in them being a net sink in spring and summer. Rewetting from a water table 60 cm deep tp 30 cm deep cut annual net emissions by 91% (abstract says 94% but see Table 2 for the correct numbers). Rewetting from to 20 cm deep switched the pocosoins from a carbon source to a sink, sequestering 3.3 t CO2e / ha / yr. Re-wetting also reduces the risk of peat fires which would increase emissions much more. Finally, Table 3 has their estimate of how much restorable peatlands (drained peatlands currently used for agriculture or forest plantations) could be re-wetted. Note that Evans et al. 2021 earlier found that raising the water table to these levels are likely to reduce crop yields (or require a switch to different crops and cultivars), but that raising the water level to the bottom of the root zone is a clear win-win.

Anderson, S., Plantinga, A., & Wibbenmeyer, M. (2020). Inequality in Agency Responsiveness: Evidence from Salient Wildfire Events (Issue December). https://www.rff.org/publications/working-papers/inequality-agency-responsiveness-evidence-salient-wildfire-events/

Comer, P. J., Hak, J. C., & Seddon, E. (2022). Documenting at-risk status of terrestrial ecosystems in temperate and tropical North America. Conservation Science and Practice, 4(2), 1–13. https://doi.org/10.1111/csp2.603

Dreiss, L. M., & Malcom, J. W. (2022). Title identifying key federal, state, and private lands strategies for achieving 30 × 30 in the United States. Conservation Letters, May 2021, 1–12. https://doi.org/10.1111/conl.12849

Dreiss, L. M., Lacey, L. M., Weber, T. C., Delach, A., Niederman, T. E., & Malcom, J. W. (2022). Targeting current species ranges and carbon stocks fails to conserve biodiversity in a changing climate: opportunities to support climate adaptation under 30x30. Environmental Research Letters, 2(1), 0–31. https://doi.org/10.1088/1748-9326/ac4f8c

Halpern, B. S., Frazier, M., Verstaen, J., Rayner, P., Clawson, G., Blanchard, J. L., Cottrell, R. S., Froehlich, H. E., Gephart, J. A., Jacobsen, N. S., Kuempel, C. D., McIntyre, P. B., Metian, M., Moran, D., Nash, K. L., Többen, J., & Williams, D. R. (2022). The environmental footprint of global food production. Nature Sustainability. https://doi.org/10.1038/s41893-022-00965-x

Hamilton, H., Smyth, R. L., Young, B. E., Howard, T. G., Tracey, C., Breyer, S., Cameron, D. R., Chazal, A., Conley, A. K., Frye, C., & Schloss, C. (2022). Increasing taxonomic diversity and spatial resolution clarifies opportunities for protecting US imperiled species. Ecological Applications, 32(3), 1–19. https://doi.org/10.1002/eap.2534

Higgins, J., Zablocki, J., Newsock, A., Krolopp, A., Tabas, P., & Salama, M. (2021). Durable Freshwater Protection: A Framework for Establishing and Maintaining Long-Term Protection for Freshwater Ecosystems and the Values They Sustain. Sustainability, 13(4), 1950. https://doi.org/10.3390/su13041950

James, R., Ariunbaatar, J., Bresnahan, M., Carlos‐Grotjahn, C., Fisher, J. R. B., Gibbs, B., Hausheer, J. E., Nakozoete, C., Nomura, S., Possingham, H., & Lyons, K. (2022). Gender and conservation science: Men continue to out‐publish women at the world’s largest environmental conservation non‐profit organization. Conservation Science and Practice, January, 1–9. https://doi.org/10.1111/csp2.12748

Nicholson, E., Watermeyer, K. E., Rowland, J. A., Sato, C. F., Stevenson, S. L., Andrade, A., Brooks, T. M., Burgess, N. D., Cheng, S.-T., Grantham, H. S., Hill, S. L., Keith, D. A., Maron, M., Metzke, D., Murray, N. J., Nelson, C. R., Obura, D., Plumptre, A., Skowno, A. L., & Watson, J. E. M. (2021). Scientific foundations for an ecosystem goal, milestones and indicators for the post-2020 global biodiversity framework. Nature Ecology & Evolution, 5(10), 1338–1349. https://doi.org/10.1038/s41559-021-01538-5

Noon, M. L., Goldstein, A., Ledezma, J. C., Roehrdanz, P. R., Cook-Patton, S. C., Spawn-Lee, S. A., Wright, T. M., Gonzalez-Roglich, M., Hole, D. G., Rockström, J., & Turner, W. R. (2022). Mapping the irrecoverable carbon in Earth’s ecosystems. Nature Sustainability, 5(1), 37–46. https://doi.org/10.1038/s41893-021-00803-6

Richardson, C. J., Flanagan, N. E., Wang, H., & Ho, M. (2022). Annual carbon sequestration and loss rates under altered hydrology and fire regimes in southeastern USA pocosin peatlands. Global Change Biology, July, 1–15. https://doi.org/10.1111/gcb.16366

Saran, S., Chaudhary, S. K., Singh, P., Tiwari, A., & Kumar, V. (2022). A comprehensive review on biodiversity information portals. Biodiversity and Conservation, 0123456789. https://doi.org/10.1007/s10531-022-02420-x
Sullivan-Stack, J., Aburto-Oropeza, O., Brooks, C. M., Cabral, R. B., Caselle, J. E., Chan, F., Duffy, J. E., Dunn, D. C., Friedlander, A. M., Fulton-Bennett, H. K., Gaines, S. D., Gerber, L. R., Hines, E., Leslie, H. M., Lester, S. E., MacCarthy, J. M. C., Maxwell, S. M., Mayorga, J., McCauley, D. J., … Grorud-Colvert, K. (2022). A Scientific Synthesis of Marine Protected Areas in the United States: Status and Recommendations. Frontiers in Marine Science, 9(May), 1–23. https://doi.org/10.3389/fmars.2022.849927

Sze, J. S., Carrasco, L. R., Childs, D., & Edwards, D. P. (2021). Reduced deforestation and degradation in Indigenous Lands pan-tropically. Nature Sustainability, 2. https://doi.org/10.1038/s41893-021-00815-2
Vijay, V., Fisher, J. R. B., & Armsworth, P. R. (2022). Co‐benefits for terrestrial biodiversity and ecosystem services available from contrasting land protection policies in the contiguous United States. Conservation Letters, February, 1–9. https://doi.org/10.1111/conl.12907

Happy New Year,


p.s. We continue to find creative ways to get by without a car. The photo shows that this year we wheeled our Christmas tree home using a dolly from a lot a bit over a mile away.