Best science summaries of 2025

Happy New Year!

As always, I’ve compiled the summaries of my favorite 15 papers from 2025 (more or less – I left out some papers I loved to make room for a more well-rounded set). I also wanted to re-share two non-paper tidbits:

1. You all sent me lots of great advice for scientists, much of which was similar to a paper I co-authored (and we have lots of companion products for that paper).
2. A case study of effective science communications (from this video overview): People struggle to understand the risk of relatively safe medical procedures (like anesthesia). The “micromort” is an activity with a one in a million chance of resulting in death (Howard 1989, “Microrisks for Medical Decision Making”), allowing you to compare risks between activities you understand and those new to you. Table 1 in Keage and Loetscher 2018 has a nice comparison of understandable risks, from 1 micromort (walking 27 miles), to going under anesthesia once (10 μmorts = walking 270 miles), to giving birth (120 μmorts), and even climbing Mt Everest (12,000 μmorts). Doctors can use this to explain risk, as in Sieber and Adams 2017 which note the risk of getting lymphoma from breast implants is lower than a day of skiing or drinking 500 mL of wine. Table 1 in Ahmad et al. 2015 has a table comparing the risk of a range of medical procedures, making a great complement to the “everyday risk” table in Keage and Loetscher (e.g., elective open heart surgery is risky, but 5 times safer than emergency open heart surgery).

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DEFORESTATION:
Franco et al. 2025 looks at how deforestation and climate change have affected temperature and precipitation in the Amazon. Losing trees not only increases atmospheric carbon which drives global warming, for tropical forests in particular it also increases LOCAL warming and especially decreases water cycling. They found that deforestation caused 3/4 of the decline in dry season precipitation but only 17% of the increase in temperature. This is similar to other work which has found deforestation has delayed the onset of the rainy season in the Cerrado (Spera et al. 2016) and Pantanal (Lázaro et al. 2020).
Roquette et al. 2025 is ostensibly about the technical details around land use mapping in Mato Grosso, Brazil. But it actually makes a much broader point: boring things like data sources and algorithms used can have an outsize backdoor policy impact. They argue that a shift in how land use was classified could sneakily allow a ton of deforestation. Basically by changing how "forest" is defined and reclassifying some forest as a type of savanna (confusingly, cerrado is an ecosystem but the Cerrado is a biome / region), this could allow deforestation since 80% of forest has to be set aside from development but only 35% of savanna does. In some cases the new map actually does the reverse (classifying what was savanna as forest) but that can be reversed upon request. The worst case scenario is that up to 4,1 million ha could be authorized for deforestation.
 

FOREST DEGRADATION:
Bourgoin et al. 2024 is a global analysis of degradation of tropical moist forests using LiDAR satellite data (from GEDI) along with Landsat optical imagery. It's worth reading the whole paper, but a few key findings: 1) degradation is hard to sense but is also a) a good predictor of deforestation in addition to b) being inherently meaningful. 2) Forest height is reduced by selective logging (15%) and fire (50%) and recovery is low after 20 years. 3) Expansion of ag and roads leads to a 20-30% drop in forest canopy height and biomass at the edge, with effects up to 1.5km in from the edge. Fig 1 has maps of global results - it's a bit confusing but the x-axis of the charts is height in meters, so lower numbers mean more degradation or younger forests. There's an article about this one at https://phys.org/news/2024-07-reveals-human-degradation-tropical-forests.html#google_vignette
 

FORESTATION (REFORESTATION AND AFFORESTATION):
Wang et al. 2025 finds that earlier estimates of how much of the world could be forested were much too high. One the one hand - this means we can't count on trees to do as much sequestering as some models hoped for. But as one of the authors (Susan Cook-Patton) points out (in this excellent post) the larger area wasn't feasible anyway, so this smaller estimate gives us more actionable priorities for planting. She also notes that while reducing fossil fuels (and protection of acutely threatened forests) is higher priority than forestation, we absolutely need all of the above. Note: reforestation is restoring trees where they used to be, afforestation is planting trees in what used to be grasslands or other ecosystems, forestation is both.


FIRE:
Ellis et al. 2022 is a global analysis of fire risk over the past 41 years, using estimated moisture trends in fuel (surface litter and dead plant debris) as the key metric. Fig 2a shows the % of days during the fire season where fuel moisture is expected to be below 10% (and thus at high fire risk), while 2b shows the total # of fire season days at high fire risk and Fig 4 shows the trend in high fire risk over time (36% of ecoregions are drying vs. only 4% getting wetter). They note that days w/ dry fuel isn't the only key driver of risk; consistent dry conditions limit fuel accumulation and thus the risk of severe fire. So surprisingly historically wet forests which accumulate lots of plant matter in wet years between fires may be the most at risk (as other research has shown).

Siquiera et al. 2025 has a helpful reminder that finer data isn't always better. They found free MODIS data (which is relatively fast and easy to process due to 500m resolution) actually did a little better at detecting areas that had burned in the Pantanal than Sentinel 2 data (also free but needs more babying and at 10m [2500* finer resolution] it takes a ton more processing time). LANDSAT (at 30m) did worse than either. The only caveat is that their validation for “burned areas” is fire foci which are partly derived from MODIS which likely biases the results somewhat. But anytime we can get away with using coarser data to save time and money it’s good news! One of my papers has a table about when coarser vs. finer data may be better, and that table is also in a blog about how to pick the right spatial resolution of data

Guzmán-Rojo et al. 2025 is an interesting model of how fires in the Bolivian Chiquitano dry forest affect water availability, focusing on soil changes (crusting, ash deposition, and reduced porosity which can decrease infiltration and increase runoff) rather than vegetation loss. They found ~40% lower recharge in the first year after a hypothetical very severe fire, returning to ~10% lower than pre-fire after two years. However, they note that field data showed that moderate to severe fires actually reduced soil porosity by 39%, while their hypothetical very severe fire assumed a 70% reduction which is probably an upper bound for how much soil permeability could be reduced. They also note that if they had accounted for vegetation loss in their model, the recharge may have been lower in some areas where dense vegetation transpires more water than it intercepts. While they had limited data to validate their model they used other studies and proxies where they could.
 

FRESHWATER
Sayer et al. 2025's headline is that 1/4 of freshwater animals are threatened with extinction. But that's similar to other estimates; to me the new thing here is guidance on how to prioritize sites to conserve with limited data. They found that 1) prioritizing with just threatened freshwater tetrapod data (animals with four legs like some amphibians, reptiles, birds, and mammals) does well for overall freshwater biodiversity (range-size rarity) but 2) prioritizing on abiotic factors alone (low flow / water stress, nitrogen as a proxy for water pollution) does worse than random! Also from Fig 2b permanent rivers are home to almost all of the threatened FW species, while species in other fresh wetlands fare much better.

Petry et al. 2025 has predictions of changing streamflow and flooding across South America by 2100 under a moderate climate change scenario. Figure 4 has the key findings about how much more or less frequent floods may be. Note that “RP” means “return period” as in a “5 year flood” or “100 year flood” (the magnitude of flooding you’d expect on that frequency / rarity, so higher numbers mean more severe flooding). RPCF means how much more or less frequent those floods would be (with negative sign indicating less frequent flooding, e.g. the -2 on the Paraguay river in the Pantanal means half as often). But much more flooding is expected in Peru, Ecuador, Colombia, and Southern Brazil, and parts of the Amazon will see 1/10 as much flooding as they historically have. They find Pantanal floods (in the Paraguay River and some tributaries like Cuiaba and Negro) will be roughly half as frequent and half as severe, they don’t have a clear trend in the Chaco, and in Chile the area from roughly Santiago to Valdivia has some rivers where flooding will be ~2-3 times less frequent while the northern part of Chile will only see slightly less flooding.
 
 
CLIMATE CHANGE - CARBON MARKETS AND ALBEDO:
Riley et al. 2025 have an update on an issue I've written about several times: that the albedo of trees (how much they reflect sunlight compared to bare soil) can reduce or even fully negate the climate benefit of trees in some cases. They looked at 172 tree planting projects in the voluntary carbon market to see how carbon credits issued compared to true climate impact once albedo was considered. On average 18% of the issued credits shouldn't have been, and 25% of the projects offered more than double the credits they should have once albedo was considered. 12% of the projects (a subset of that 25%) were even net harmful (representing 30% of total credits issued). In good news, 9% of projects actually had more benefit than estimated, and over half of projects had 0-25% of their issued carbon credits negated by albedo. This is important to get right, but a shortcut is to focus protection and forestation in more tropical places while avoiding areas with heavy snow cover and/or very light-colored soils (the pink places in Fig 2a are good to avoid).


CATTLE AND CLIMATE CHANGE:
Meo-Filho et al. 2024 is an important study (part of a special issue of papers around the sustainability of animal foods and plant alternatives, https://www.pnas.org/topic/561). There's been lots of research with hyperbolic claims about red algae reducing methane production in cattle (mostly in vitro, or tests in a petri dish). I believe this is the first paper to measure methane reductions not only 1) in vivo (a test of what happens in real animals) but 2) in the grazing phase of their life cycle. Most American cattle graze for very roughly 15 months before spending 3 months in a feedlot, and they emit more methane per day when grazing. Only 15% of total cattle production GHGs come from the feedlot phase, so even big reductions then can't touch cattle's high carbon footprint. But this paper found supplementing with seaweed reduced GHGs relative to control animals by 38% over 90 days with no side effects! That is great news and this is work worth following up, BUT a few key caveats: 1) this was a study of only 24 animals, 2) the animals began at 15 months when they would typically go to a feedlot, to show how much this could really reduce the total carbon footprint of cattle (and if any side effects crop up eventually) it would need to be tested on calves from when they are weaned off of milk to when they go to slaughter, and 3) variations in cattle breed, the dominant type of grass they're eating, and climate could all affect the results. So it's very good news, but does not yet mean it's possible to produce a burger w/ 1/3 less carbon. Also, while the numbers are hotly contested, remember that the carbon footprint of beef is very roughly 10* that of pork or chicken (~50* the GHG of beans), so even if the reduction IS scalable, beef will still be a high carbon food.
 

BIODIVERSITY OFFSETTING:
While Lourival et al. 2025 ponders 10 questions for biodiversity offsetting in the Brazilian Pantanal and its watershed (listed at the top of the 3rd page), it's relevant to biodiversity offsets in general. I especially like Fig 4 with different ways to think about equivalence for offsets (area, economic value, ecosystem value, or a mix). So for example if you clear high-value land in the Cerrado, you could need to protect a much larger lower-value area in the Pantanal. They find 57% of properties in the highlands feeding the Pantanal are out of compliance with the Forest Code (Table 1, Fig 3). Properties WITHIN the Pantanal are only 22% out of compliance, so considering the whole river basin could offer opportunities BUT ecological equivalence may be low and state regulations restrict what is possible. One could argue that's a huge market for offset purchases OR evidence the law is toothless and demand will be low.
 

GLOBAL THREATS:
Oakleaf et al. 2024 is a long-awaited global analysis of likelihood of short-term (by 2030) habitat conversion (1 km resolution, see Fig 5 for the results). They include not only cropland and city expansion, but also land use change for energy (fossil or renewable) and mining, and considered several suitability factors (like slope and land cover). Their approach assumes recent trends (2000-2015) will continue rather than modeling different scenarios of economic development. Like any global data you can find places where it seems wrong, but it's a great resource nonetheless. You can grab the data or view the data in a web map. There's also a blog about the paper.
 

WILDLIFE:
Kopf et al 2024 really made me think. They summarize some of the important contributions of old (and often "wise"!) animals, and proposes "longevity conservation" as a strategy to retain them. Old animals are especially important for species who rely on cultural transmission (like migratory species) and those who reproduce more as they age and grow, and the article goes into detail with examples of both. The article also covers some of the impacts of losing large and old animals, like changing ecosystem structure and function, pack instability, and even infanticide. The ability of older animals to help their group adapt to drought or food shortages maybe increasingly important as climate changes (although the individual resilience of older animals is likely to lower to some stresses like disease). With trophy hunting and fishing selecting for larger (typically older) animals, they argue for the importance of better population modeling, setting age class targets for fisheries, restricting hunting of larger and older animals, and going beyond tracking biomass or abundance to watch for "longevity depletion."
 

CHOCOLATE:
Gopaulchan et al. 2025 advances the frontier of scientific understanding of flavor development in chocolate. It has a few components. First they measured changes in temperature and pH over a week in fermenting Colombian cacao beans to estimate microbial activity (they correlated with the color changes used to assess fermentation end point). Second they sequenced the genome every 24 hours to watch diversity decline for both bacteria (Fig 1e, Acetobacteraceae dominating over time) and fungi (Fig 1f, Saccharomycetaceae dominating over time). But crucially, they third compared how these shifts happened at three farms w/ similar genetics but different microbial mixes. Look at Fig 2e and 2f!!! The two new farms had diversity increase again eventually, and one farm had significant populations of families that were only present in trace amounts before! OK, stay with me. Fourth, they extracted cocoa liquor and compared their three farms to reference chocolates (Fig 3b). One farm tastes "West African" (roasty, dark wood, tobacco), and two taste more "Malagasy" (one emphasizing light / caramelly / tropical flavors, and the other more fruity and bitter). Fifth they figured out which families of microbes were likely most essential for flavor (Fig 4) and sixth put together different inoculant mixes (most had the full diversity of microbes minus a different single strain missing for each mix, plus a random mix). They then (seventh) did controlled cacao bean fermentation w/ each mix plus an uninoculated control (in the lab so it wouldn't have the wild strains), and tasted the results (eighth), finding that the beans inoculated with the full mix of strains had better flavors than those inoculated w/ fewer strains or none at all (Fig 5h). The authors argue that with synthetic starters and controlled fermentation, chocolate flavor could be improved in more industrial-scale chocolate.
 
 
REFERENCES:
Bourgoin, C., Ceccherini, G., Girardello, M., Vancutsem, C., Avitabile, V., Beck, P. S. A., Beuchle, R., Blanc, L., Duveiller, G., Migliavacca, M., Vieilledent, G., Cescatti, A., & Achard, F. (2024). Human degradation of tropical moist forests is greater than previously estimated. Nature, 631(8021), 570–576. https://doi.org/10.1038/s41586-024-07629-0

Ellis, T. M., Bowman, D. M. J. S., Jain, P., Flannigan, M. D., & Williamson, G. J. (2022). Global increase in wildfire risk due to climate‐driven declines in fuel moisture. Global Change Biology, 28(4), 1544–1559. https://doi.org/10.1111/gcb.16006

Franco, M. A., Rizzo, L. V., Teixeira, M. J., Artaxo, P., Azevedo, T., Lelieveld, J., Nobre, C. A., Pöhlker, C., Pöschl, U., Shimbo, J., Xu, X., & Machado, L. A. T. (2025). How climate change and deforestation interact in the transformation of the Amazon rainforest. Nature Communications, 16(1), 7944. https://doi.org/10.1038/s41467-025-63156-0

Gopaulchan, D., Moore, C., Ali, N., Sukha, D., Florez González, S. L., Herrera Rocha, F. E., Yang, N., Lim, M., Dew, T. P., González Barrios, A. F., Umaharan, P., Salt, D. E., & Castrillo, G. (2025). A defined microbial community reproduces attributes of fine flavour chocolate fermentation. Nature Microbiology, 10(9), 2130–2152. https://doi.org/10.1038/s41564-025-02077-6

Guzmán-Rojo, M., Silva de Freitas, L., Coritza Taquichiri, E., & Huysmans, M. (2025). Groundwater Vulnerability in the Aftermath of Wildfires at the El Sutó Spring Area: Model-Based Insights and the Proposal of a Post-Fire Vulnerability Index for Dry Tropical Forests. Fire, 8(3), 86. https://doi.org/10.3390/fire8030086

Kopf, R. K., Banks, S., Brent, L. J. N., Humphries, P., Jolly, C. J., Lee, P. C., Luiz, O. J., Nimmo, D., & Winemiller, K. O. (2024). Loss of Earth’s old, wise, and large animals. Science, 2705, 1–19. https://doi.org/10.1126/science.ado2705

Lourival, R. F. F., de Roque, F. de O., Bolzan, F. P., Guerra, A., Nunes, A. P., Lacerda, A. C. R., Nunes, A. V., Alves, A., Filho, A. C. P., Ribeiro, D. B., Eaton, D. P., Brito, E. S., Fischer, E., Neto, F. V., Porfirio, G., Seixas, G. H. F., Pinto, J. O. P., Quintero, J. M. O., Sabino, J., … Tomas, W. M. (2025). Ten relevant questions for applying biodiversity offsetting in the Pantanal wetland. Conservation Science and Practice, July 2022, 1–21. https://doi.org/10.1111/csp2.13274

Meo-Filho, P., Ramirez-Agudelo, J. F., & Kebreab, E. (2024). Mitigating methane emissions in grazing beef cattle with a seaweed-based feed additive: Implications for climate-smart agriculture. Proceedings of the National Academy of Sciences, 121(50), 2–9. https://doi.org/10.1073/pnas.2410863121

Oakleaf, J., Kennedy, C., Wolff, N. H., Terasaki Hart, D. E., Ellis, P., Theobald, D. M., Fariss, B., Burkart, K., & Kiesecker, J. (2024). Mapping global land conversion pressure to support conservation planning. Scientific Data, 11(1), 830. https://doi.org/10.1038/s41597-024-03639-9

Petry, I., Miranda, P. T., Paiva, R. C. D., Collischonn, W., Fan, F. M., Fagundes, H. O., Araujo, A. A., & Souza, S. (2025). Changes in Flood Magnitude and Frequency Projected for Vulnerable Regions and Major Wetlands of South America. Geophysical Research Letters, 52(5). https://doi.org/10.1029/2024GL112436

Riley, L. M., Cook-Patton, S. C., Albert, L. P., Still, C. J., Williams, C. A., & Bukoski, J. J. (2025). Accounting for albedo in carbon market protocols. Nature Communications, 16(1), 8810. https://doi.org/10.1038/s41467-025-64317-x

Roquette, J. G., Vacchiano, M. C., Daher, F. R. G., & Finger, Z. (2025). Pseudo-legal deforestation due to changes in the classification of native vegetation in Mato Grosso, Brazil. Environmental Conservation, 1–7. https://doi.org/10.1017/S037689292510012X

Sayer, C. A., Fernando, E., Jimenez, R. R., Macfarlane, N. B. W., Rapacciuolo, G., Böhm, M., Brooks, T. M., Contreras-MacBeath, T., Cox, N. A., Harrison, I., Hoffmann, M., Jenkins, R., Smith, K. G., Vié, J.-C., Abbott, J. C., Allen, D. J., Allen, G. R., Barrios, V., Boudot, J.-P., … Darwall, W. R. T. (2025). One-quarter of freshwater fauna threatened with extinction. Nature, 3(December 2023). https://doi.org/10.1038/s41586-024-08375-z

Siqueira, R. G., Moquedace, C. M., Silva, L. V., de Oliveira, M. S., Cruz, G. D. B., Francelino, M. R., Schaefer, C. E. G. R., & Fernandes-Filho, E. I. (2025). Do finer-resolution sensors better discriminate burnt areas? A case study with MODIS, Landsat-8 and Sentinel-2 spectral indices for the Pantanal 2020 wildfire detection. International Journal of Remote Sensing, 00(00), 1–24. https://doi.org/10.1080/01431161.2025.2496000

Wang, Y., Zhu, Y., Cook-Patton, S. C., Sun, W., Zhang, W., Ciais, P., Li, T., Smith, P., Yuan, W., Zhu, X., Canadell, J. G., Deng, X., Xu, Y., Xu, H., Yue, C., & Qin, Z. (2025). Land availability and policy commitments limit global climate mitigation from forestation. Science, 389(6763), 931–934. https://doi.org/10.1126/science.adj6841


Sincerely,
 
Jon

 
p.s. I found these Christmas decorations at the Carnegie Hotel in New York especially striking b/c of the contrast w/ the dark background, lights, and glittery balls

Best of 2023 science summaries

Happy new year!

As usual here are my favorite 15 articles from 2023, and a few other things you may have missed.

But first - if you or someone you know are looking for a sweet and loving dog in your life (or two?), both of our foster dogs Luna (top head above) and Kong (supporting head) are still up for adoption! You can read about Kong, see how cute he is, read about Luna, and see how cute she is.

1. A summary of the IPCC's latest report (AR6) came out, click here for my brief summary of that summary
2. The earth had its first day that was 2C warmer than the historic pre-industrial average (1850-1900). We're still a ways from an AVERAGE of 2C warmer than pre-industrial, but still a bummer.
3. Last month I shared some (not very well-informed) thoughts about how I'm using artificial intelligence (AI), specifically large language models (LLMs) like ChatGPT and Google's Bard. Scroll to the bottom of my December summary  to see them

On to the science articles!

PEOPLE AND NATURE:
Chaplin-Kramer et al. 2022 is a great global summary of 14 ecosystem services I've been waiting to see for years! Their big finding is that 90% of nature's local contributions to people within each country come from a total of 30% of global land area and 24% of coastal waters (EEZs). Globally only 15% of those places are protected. The land and water needed is uneven by country (e.g., the US needs 37% of land and 15% of coastal waters), and protection varies too. See Fig 1 for the areas that provide the most benefit per unit area. The land required would be lower if optimizing globally, but at the cost of less equitable benefit distribution. The 2 global ones (carbon storage and moisture recycling) need 44% of land (optimized globally) to stay at 90% of current levels, mostly overlapping with the 30% (see Fig 3). Roughly 87% of the world population benefits from at least one of the ecosystem services, but benefits are not distributed equally (see Fig 2). The local services include: water quality (regulating nitrogen and sediment), crop pollination, livestock fodder, production of timber and fuelwood, flood regulation, fish harvest (from rivers and oceans), recreation (on land and oceans), and coastal risk reduction. If interested you can get combined GIS data from https://osf.io/r5xz7/?view_only=d611a688525f4ceb8db4ef4e7528b0e8 or one of the authors (Rachel Neugarten) is happy to send individual maps and data.

Cinner et al. 2019 is a 16 year study of rotational fishing / closure in Papua. They found success in compliance with the system (due to strong social cohesion driven by leaders sharing info, a "carrot and stick" approach, and lots of community participation) BUT even though closed areas rebounded, over the study period fish biomass dropped by about half. So even though the closure program worked as intended, it wasn't enough to offset overfishing when areas were open.

Grenz & Armstrong 2023 is an article criticizing "pop-up restoration," a term they coin for ecological restoration that 1) lacks long-term engagement and monitoring, 2) denies people use of lands (even Indigenous people who have been there for millennia), and 3) sets fixed ecological baselines or goals even for ecosystems which historically were highly managed and dynamic. They describe two use cases where  management outcomes preferred by Indigenous people were ignored, instead managing for outcomes preferred by non-Indigenous ranchers or residents. They call for restorative justice being the norm, and ethical engagement with communities in each specific place (rather than coopting and misusing Indigenous knowledge). They also call for more openness to evolving needs and conditions of both people and ecosystems, and acknowledging failures and wrongdoing.


GENDER AND CONSERVATION:
James et al. 2023 asked over 900 science & conservation staff of The Nature Conservancy about their careers and influence, and how they perceived their gender as impacting that. We found that women had less influence, experienced many barriers to their careers (including harassment, discrimination, and fear of retaliation for speaking out), and that men overestimated gender equity. Only have 5 minutes? Skip to the recommendations on page 7 (we ask orgs to: show public leadership on equity, improve transparency and accountability, diversify teams and improve career pathways for women, be flexible, include training and mentoring as part of broader change, help women connect, address sexual discrimination and harassment, and consider intersectionality). If you have 15 minutes more, read the quotes in Table 2 (p5-8) because they're really compelling and illustrative. Or if you're with the half of men and 3/4 of women in our sample who think we have more to do on gender equity (rather than that we've already "gone overboard" or that it's not an issue as some men reported), just read the whole damn paper because there's a lot of interesting detail and nuance in the results. I learned a ton while helping out on it, and I'm excited to start advocating for the recommendations. You can read it at: https://bit.ly/TNCgenderpaper or a short blog at https://blog.nature.org/science-brief/gender-bias-holds-women-back-in-conservation-careers/ 


SCIENCE COMMUNICATIONS:
Toomey et al. 2023 is a nice reminder that just sharing information doesn't usually change minds. They challenge the idea that facts & scientific literacy lead to research being applied, and that broad communications targeting as many individuals as possible are the most effective way to share those facts. Instead they recommend appealing to values and emotions, and strategically targeting audiences by considering social networks (drawing on science about behavior change) and social norms. I love the conclusion that "this article may not change your mind" but that they hope it will inspire reflection. I also like the use of the backronym WEIRD (Western, Educated, Industrialized, Rich, Democratic) to describe countries like the US.


LEARNING FROM FAILURE:
Dickson et al. 2023 piqued my curiosity by breaking down different causes of conservation failure and how to respond. I generally dislike taxonomy papers, and find them academic and hard to apply. But understanding how to respond to different kinds of failure seems helpful, especially for the most common causes (including lacking a sufficiently robust theory of change. see table 2 for more). Their taxonomy has 59 (!) root causes, grouped into 6 categories: 1) planning, design, or knowledge (e.g., inadequate theory of change); 2) team dynamics (e.g., disagreements on what priorities should be); 3) project governance (e.g., lack of a technical advisory group); 4) resources (e.g., staff overloaded or lack needed technical expertise); 5) stakeholder relationships (e.g., lack of buy-in from gov't); and 6) unexpected external events (e.g., natural disaster, war, disease, etc.). After reading all the ways to fail, my main take away is that failure will happen sometimes and we need to focus on how to learn and pivot. The other big one is that while teams often resent spending a few hours developing and refining a theory of change (ToC), that is likely time well spent given that how often an insufficient ToC was listed as a cause of failure.


CLIMATE MITIGATION:
Duncanson et al. 2023 estimates how much global forested protected areas may be reducing climate change. They matched forested protected areas to similar forested unprotected areas using data from 2000 (land cover, ecoregion, and biome; with additional control pixels that accounted for population etc. - see Table S1). Then they used the new (2019) GEDI lidar data to estimate aboveground forest biomass in 2020. 63% of forested PAs had significantly higher biomass than matched unprotected areas; on average PAs have 28% more aboveground biomass. Over a third of that effect globally comes from Brazil; Africa had less C dense forests and more human pressures on both PAs and unprotected areas. As you'd guess, most of the difference in unprotected sites was due to deforestation. But in 18% of PAs carbon was higher than unprotected sites even though optical sensors didn't detect deforestation (implying LiDAR is detecting either avoided degradation and/or enhanced growth in PAs). As a final note, other research has shown that both ICESat-2 and GEDI LiDAR satellites tend to underestimate forest canopy heights (mostly irrelevant here given the matching approach, but good to know for other global estimates).

Knauer et al. 2023 has good news - better modeling estimates forests could sequester more carbon than we thought. But it's likely very small good news. Their best case is 20% more "gross primary productivity" (GPP, energy captured by photosynthesis), BUT a) that's using an extremely unlikely 'worst case' cliamte scenario which is actually hard to achieve, (RCP8.5) and b) only a fraction of GPP ends up sequestered as carbon (see Cabon et al. 2022 for more). Since forests offset roughly 25% of annual human emissions, the results likely mean <1% of annual emissions could be offset. I'll take it, but we still need to reduce gross emissions as fast as possible.


CLIMATE RESILIENCE:
Rubenstein et al. 2023 is a systematic review of how documented range shifts (when plants and animals change where they live, presumably in response to climate change) compare to predictions. Across 311 papers, only 47% of shifts due to temperature were in expected directions (higher latitudes & elevations, and marine movement to deeper depths was seen but was non-significant). See Fig 4 for how results varied by taxonomic group, ecoystem type, and type of shift. Not many studies looked at precip but of those that did only 14% found species moving to stay in a precip niche. Note: this means simple assumptions of how species will move are of limited value, but NOT that local or regional predictions are inherently flawed. The authors note that considering local predictions of changing temp and precip will often depart from these simple assumptions, and other factors like water availability, fire, etc. are likely to be relevant. A final note on the last page was helpful: not all range shifts have equal relevance to management. In some cases a few individuals are moving to new places but most of the wildlife population doesn't shift at all. Both shifts AND non-shifts have implications for how management should change to keep species and ecosystems healthy! This paper has a LOT of nuance and variation in this paper, and a very detailed methods section with good recommendations for how scientists should continue these investigations


FRESHWATER:
Dethier et al 2023 (briefly summarized in Walmsley 2023) finds that mining in tropical countries is dramatically increasing sediment in rivers. 80% of the 173 rivers affected by mining that they studied had sediment concentrations more than double what they were prior to mining. This is a pretty coarse estimate using satellite data, so the actual sediment estimates are very rough, but the general pattern should be valid.


BIODIVERSITY:
NatureServe's 2023 Biodiversity in Focus US report is a high level look at threatened species (imperiled or vulnerable) in the US. It's short and worth reading the whole thing. They find 34% of plant species and 40% of animal species are threatened, and 41% of the ~400 ecosystem groups in the US are at risk of "range-wide collapse" (meaning being replaced or substantially transformed). Figure 1 and 2 have breakdowns of averages for plants and animals by subgroups. For plants cacti are the worst off at 48% threatened and sedges are the least threatened at 14%. Freshwater snails are the most threatened animals (75%, and other FW groups are all more threatened than average) while birds are the least threatened (12%) and bees are about average (37%). Note that % of species that are threatened is different than looking at % of individual organisms or biomass that is threatened (all are useful metrics, Audubon's State of the Birds report looks at trends in bird population size). Figure 3 shows the most and least threatened ecosystems; unsurprisingly virtually all tropical ecosystems are threatened (they had relatively small extents originally, and are valuable for agriculture), while cliffs / rock and alpine and tundra ecosystems fare the best due to less threat of conversion to other land uses and higher rates of protection (Figure 5). They don't provide details but I would guess these are relatively short-term predictions, as climate change will threaten a lot of alpine and tundra ecosystems in the long term. Figure 4 shows how protected different species groups and ecosystems are. Almost 30% of vascular plant species are protected >50% of their range, but only 15% of vertebrate species are that protected. Finally, Figure 9b shows which states have the highest % of their area in at-risk ecosyetsms (NE, MT, and SD score the highest due to large at-risk grasslands), and Figure 11 shows priority areas for conserving imperiled species. With some exceptions (like FL) Figures 9 and 11 highlight different priority areas; Fig 11 focuses on relatively small and irreplaceable places that the most threatened species rely on, while Fig 9 focuses on more intact and lower diversity ecosystems that are at risk of being transformed (but with less potential for species extinctions). The authors conclude that the Restoring America's Wildlife Act (RAWA) guided by State Wildlife Action Plans (SWAPs) is our best bet to catalyze massive investment in conservation of the places that need it most.


WILDLIFE MANAGEMENT:
Jewell et al. 2023 surveyed directors and board members in charge of state wildlife agencies in the SE U.S. about future conservation challenges and how they plan to respond. They found that the respondents were focused on funding and 'agency relevance' (including changing values and fewer hunters) but less concerned about climate change (see Table 2). One quote stuck out at me, which was that they saw climate change impacts as important at time-scales beyond decades, and thus not urgent to act on (they also saw it as too political). By comparison, they saw education and outreach as critical to recruit hunters and tell the public the value of hunting and fishing. Agency directors average 5 years in office, so short-term things they can do may be more appealing. The authors call for engaging decision makers around the science of how climate change is already affecting wildlife, how that is expected to shift over time, and what actions or preparations can be taken now to help.

I couldn't resist reading Clark et al. 2023 right away despite my sad backlog. I once had a native plant garden guy tell me "at best non-native plants offer no value to pollinators and other wildlife, and most are harmful." Obviously false as an absolute! But how do they compare? Clark looked at 10 species in a Connecticut forest and found some invasive species (like honeysuckle) had more bugs (mass and protein) than the average for natives, but others (Japanese barberry) had fewer bugs. But birds seemed to forage both equally. It's a tiny study and I wish they hadn't pooled all native species, but I do like a study that counters "it depends!" to a truism in conservation.


FORESTS & FIRE:
Prichard et al. 2021 is a review of several questions related to fire in US western forests (see Table 1 for the summary of questions & answers). They include whether and when/ how to use cutting trees and prescribed burns as tools for reducing wildfire risk and/or climate mitigation and/or ecological restoration. The authors argue that many dry forests (and some moist forests mixed into dry forest landscapes) historically experienced more frequent fires of low to moderate intensity (often set by Native Americans), but that these forests are now denser and more likely to have severe crown fires (especially as summers become warmer and drier). That in turn will cause some forests to be lost and shift to grasslands or other ecosystems. Read Table 1 for key takeaways, including that for many (not all) Western forests, thinning and prescribed burning are important tools. Side note: given the active debate on this topic, I asked for input from a few forest scientists deep in the lit, and they recommended this article.


METASCIENCE:
Breznau et al. 2022 has some scary news about science - not only is it less reproducible than we think, we can't even figure out why results vary so much. To be fair, they note that natural sciences and/or experimental research should have less variation than social science based on existing surveys (what this study looked at). But it's still concerning! Or preliminarily concerning but waiting for many more replicas, to take their message to heart. The models the 73 teams built were: 17% positive (more immigration increases support for social policies), 25% negative (more immigration reduces support for social policies), and 58% did not find a clear effect (the confidence interval included zero, although they may have had a positive or negative average effect). 61% of researchers concluded that immigration does not reduce support for social policies, 26% concluded it DOES reduce support (the text says 28.5% but it's a typo, reinforcing the core message of the paper), and 13% concluded it couldn't be tested w/ the given data. And Fig 2 shows that not only are results and conclusions all over the place, the variation isn't explained by the variables they tracked like expertise or prior beliefs. That means researcher bias is only part of the problem. I have some questions about the metanalysis itself that make me suspect they could have explained more of the variance with different methods (ironically, that is consistent with their core findings about how small method changes can drive results). But the paper reveals two problems: 1) scientists can produce different quantitative results from the same data and hypotheses, and 2) scientists' conclusions are often not well tied to their results (this paper found only ~1/3 of variation in conclusions came from how consistent the set of models each team used were). I see a lot of #2 when I peer review papers. Let's all remain humble and skeptical, and look for more replication in 2023!


REFERENCES:
Breznau, N., Rinke, E. M., Wuttke, A., Nguyen, H. H. V, Adem, M., Adriaans, J., Alvarez-Benjumea, A., Andersen, H. K., Auer, D., Azevedo, F., Bahnsen, O., Balzer, D., Bauer, G., Bauer, P. C., Baumann, M., Baute, S., Benoit, V., Bernauer, J., Berning, C., … Żółtak, T. (2022). Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty. Proceedings of the National Academy of Sciences, 119(44), 1–8. https://doi.org/10.1073/pnas.2203150119

Chaplin-Kramer, R., Neugarten, R. A., Sharp, R. P., Collins, P. M., Polasky, S., Hole, D., Schuster, R., Strimas-Mackey, M., Mulligan, M., Brandon, C., Diaz, S., Fluet-Chouinard, E., Gorenflo, L. J., Johnson, J. A., Kennedy, C. M., Keys, P. W., Longley-Wood, K., McIntyre, P. B., Noon, M., … Watson, R. A. (2022). Mapping the planet’s critical natural assets. Nature Ecology & Evolution, 7(1), 51–61. https://doi.org/10.1038/s41559-022-01934-5

Cinner, J. E., Lau, J. D., Bauman, A. G., Feary, D. A., Januchowski-Hartley, F. A., Rojas, C. A., Barnes, M. L., Bergseth, B. J., Shum, E., Lahari, R., Ben, J., & Graham, N. A. J. (2019). Sixteen years of social and ecological dynamics reveal challenges and opportunities for adaptive management in sustaining the commons. Proceedings of the National Academy of Sciences, 116(52), 26474–26483. https://doi.org/10.1073/pnas.1914812116

Clark, R. E. (2023). Are native plants always better for wildlife than invasives? Insights from a community-level bird- exclusion experiment. Preprint available at https://www.researchsquare.com/article/rs-3214373/v1

Dethier, E. N., Silman, M., Leiva, J. D., Alqahtani, S., Fernandez, L. E., Pauca, P., Çamalan, S., Tomhave, P., Magilligan, F. J., Renshaw, C. E., & Lutz, D. A. (2023). A global rise in alluvial mining increases sediment load in tropical rivers. Nature, 620(7975), 787–793. https://doi.org/10.1038/s41586-023-06309-9

Dickson, I., Butchart, S. H. M., Catalano, A., Gibbons, D., Jones, J. P. G., Lee‐Brooks, K., Oldfield, T., Noble, D., Paterson, S., Roy, S., Semelin, J., Tinsley‐Marshall, P., Trevelyan, R., Wauchope, H., Wicander, S., & Sutherland, W. J. (2023). Introducing a common taxonomy to support learning from failure in conservation. Conservation Biology, 37(1), 1–15. https://doi.org/10.1111/cobi.13967

Duncanson, L., Liang, M., Leitold, V., Armston, J., Krishna Moorthy, S. M., Dubayah, R., Costedoat, S., Enquist, B. J., Fatoyinbo, L., Goetz, S. J., Gonzalez-Roglich, M., Merow, C., Roehrdanz, P. R., Tabor, K., & Zvoleff, A. (2023). The effectiveness of global protected areas for climate change mitigation. Nature Communications, 14(1), 2908. https://doi.org/10.1038/s41467-023-38073-9

Grenz, J., & Armstrong, C. G. (2023). Pop-up restoration in colonial contexts: applying an indigenous food systems lens to ecological restoration. Frontiers in Sustainable Food Systems, 7(September), 1–12. https://doi.org/10.3389/fsufs.2023.1244790

James, R., Fisher, J. R. B., Carlos-Grotjahn, C., Boylan, M. S., Dembereldash, B., Demissie, M. Z., Diaz De Villegas, C., Gibbs, B., Konia, R., Lyons, K., Possingham, H., Robinson, C. J., Tang, T., & Butt, N. (2023). Gender bias and inequity holds women back in their conservation careers. Frontiers in Environmental Science, 10(January), 1–16. https://doi.org/10.3389/fenvs.2022.1056751 or https://bit.ly/TNCgenderpaper

Jewell, K., Peterson, M. N., Martin, M., Stevenson, K. T., Terando, A., & Teseneer, R. (2023). Conservation decision makers worry about relevancy and funding but not climate change. Wildlife Society Bulletin, November 2022, 1–14. https://doi.org/10.1002/wsb.1424

Knauer, J., Cuntz, M., Smith, B., Canadell, J. G., Medlyn, B. E., Bennett, A. C., Caldararu, S., & Haverd, V. (2023). Higher global gross primary productivity under future climate with more advanced representations of photosynthesis. Science Advances, 9(46), 24–28. https://doi.org/10.1126/sciadv.adh9444

NatureServe. (2023). Biodiversity in Focus: United States Edition. https://www.natureserve.org/sites/default/files/NatureServe_BiodiversityInFocusReport_medium.pdf

Prichard, S. J., Hessburg, P. F., Hagmann, R. K., Povak, N. A., Dobrowski, S. Z., Hurteau, M. D., Kane, V. R., Keane, R. E., Kobziar, L. N., Kolden, C. A., North, M., Parks, S. A., Safford, H. D., Stevens, J. T., Yocom, L. L., Churchill, D. J., Gray, R. W., Huffman, D. W., Lake, F. K., & Khatri‐Chhetri, P. (2021). Adapting western North American forests to climate change and wildfires: 10 common questions. Ecological Applications, 31(8). https://doi.org/10.1002/eap.2433

Rubenstein, M. A., Weiskopf, S. R., Bertrand, R., Carter, S. L., Comte, L., Eaton, M. J., Johnson, C. G., Lenoir, J., Lynch, A. J., Miller, B. W., Morelli, T. L., Rodriguez, M. A., Terando, A., & Thompson, L. M. (2023). Climate change and the global redistribution of biodiversity: substantial variation in empirical support for expected range shifts. Environmental Evidence, 12(1), 7. https://doi.org/10.1186/s13750-023-00296-0

Toomey, A. H. (2023). Why facts don’t change minds: Insights from cognitive science for the improved communication of conservation research. Biological Conservation, 278(December 2022), 109886. https://doi.org/10.1016/j.biocon.2022.109886

Walmsley, B. (2023). Satellite images show the widespread impact of mining on tropical rivers. Nature, 620(7975), 729–730. https://doi.org/10.1038/d41586-023-02349-3

Sincerely,
 
Jon

Best of 2022 science summary

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!


CONSERVATION PRIORITIES / 30x30:
Biodiversity
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!
 
Marine
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/
 



PROTECTED AREAS EFFECTIVENESS:
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.


ECOSYSTEM INDICATORS:
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.

EQUITY:
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/


FRESHWATER CONSERVATION:
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/


FOOD / AGRICULTURE:
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.



CLIMATE MITIGATION – PEATLANDS:
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.






REFERENCES:
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,

Jon

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.

Best of 2021 science summaries

 

Happy New Year!

I hope you got some time off of work and managed to stay healthy, whatever the end of the year was like for you.

As usual, I'm kicking the new year off by providing summaries for my favorite 15 articles of 2021, so that if you missed any of them you get another chance to check them out.

Also, this isn't a science article per se, but I helped to plan two webinars in 2021 with different experts providing their insights on how to best improve the impact of research (building on my 2020 paper on this topic), and I learned a ton from both. I hosted the first one (https://vimeo.com/506194985), and my colleague Peter Edwards hosted the next one (focused on Latin America, the Caribbean, and African contexts, https://vimeo.com/617423733). I've added links to the videos on this blog post where I've been collecting some related resources on the topic: http://impactblog.sciencejon.com/

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon. Here are the papers in alphabetical order (by author):

Barnes et al. 2018 highlights the downside of area targets: they may drive siting protected areas (PAs) in bad places and poor enforcement / management. They promote a shift to outcome-based protected area targets (meaning the targets are about biodiversity gains or avoided losses), emphasizing representation and connectivity, and building the evidence base for which factors affect how well PAs deliver conservation outcomes.

Dieckman et al. 2021 surveyed people about how important different social and cultural issues were to government decision makers vs. the general public. Respondents thought that government decision makers care the most about economic aspects, but that the public cares more about other social and cultural aspects. More tangible impacts (like water quality and physical safety) were perceived to be more important than intangible ones (like emotional health and local practices). Interestingly, biodiversity had the lowest perceived support second only to native culture.

Dobrowski et al. 2021 analyzes how much of the world will experience enough climate change to effectively shift into a different ecoregion, and how that relates to protected areas (PAs). They move ecoregions' location to keep their historic climate similar, which is an interesting thought exercise but not a likely scenario (given variations in soil and topography and other factors that will not shift w/ climate). They found that with 2C warming, 54% of land will effectively change ecoregions, with 22% shifting biomes (see Fig 4 for how this affects % protected by biome). This means there are winners and losers, with the biggest losers the ~5% of land within PAs that don't have an analogous climate w/in 2000 km for species to migrate to (shown in black in Figs 2b & 3b; 56 ecoregions 'disappear'). They recommend a focus on unmodified areas expected to be climatically stable that are currently underprotected, as well as areas that improve climate connectivity (see Fig 6 for a case study in the NW US and Canada). They also have a tool where you choose a place, and it'll tell you what other place currently has the climate the first place is expected to have w 2C (or 4C) warming: https://plus2c.org/

Ellis et al. 2021 argue that protecting untouched or unmodified habitat from people is a fundamentally flawed framing, b/c most habitat on earth has been to some degree inhabited by (and modified by) people for thousands of years). It's a good point that what we consider 'natural' is subjective and arbitrary (e.g. the grasslands of the Midwestern U.S. are a result of thousands of years of intentionally set fires and other impacts by Indigenous people), and modified ecosystems may have higher species richness or other metrics. They have great data on how much habitats and land use have changed over time (check out all the figures for that), and make an excellent case about how wrong it is to depict human use of nature as a recent despoiling of human-free places. They further argue that current biodiversity losses come from "the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies" and that the solution lies in empowering the stewardship of Indigenous people and local communities. I agree that opinions about which kind of ecosystem and land use is "good" are subjective, that there are good social and human rights reasons to support local autonomy, and that typically local and Indigenous people use natural areas in a way more compatible with biodiversity than how people from elsewhere tend to. I think it's also worth recognizing that even Indigenous people have consistently caused some extinctions (of large mammals in particular) when they first arrived to actually uninhabited ecosystems, and that in some cases they currently support the same kind of intensification associated with colonialism. So local autonomy will not always be a recipe for maintaining ecosystems more or less as they currently are, although there are plenty of valid opinions about which human and ecosystem outcomes conservation organizations should work to support. I'd definitely recommend reading the paper, and I realize I have a lot of listening and learning to do on the subject of Indigenous-led conservation.

Evans et al. 2021 estimated how to reduce greenhouse gases (GHGs) by raising water levels in peatlands which have been drained for agriculture. They found raising the water table by 10cm (re-wetting the peat) reduces net greenhouse gases (GHGs) by an average of 3 t CO2e/yr until it rises to a depth 30cm, from 30cm-8cm rising methane results in smaller net GHG benefits, and <8cm GHGs become net positive (see Fig 1). Cutting the water table depth in half globally (raising it to an average of 45cm in croplands and 25cm in grasslands) would cut emissions from drained peat by about 2/3 (from 786 Mt [aka MMT] CO2e/yr to 278 MT CO2e/yr). These are conservative estimates (leaving out N2O and reduced emissions from avoided deep fires), although the range of those estimates is huge (see Table 1). Alternatively re-wetting all peat up to 10cm would eliminate almost all peat emissions and likely even drive them slightly negative (15 Mt CO2e/yr). However, cutting water table depth in half would flood part of the root zone for most crops and regions, which would reduce yield. But raising the water table to just below the root zone could have big GHG benefits and potentially even improve crop resilience to drought. This is a big opportunity!

Grantham et al. 2020 estimates how much forests have been fragmented and modified around the world. They look at proximity to infrastructure, agriculture, and tree cover loss, along with lost forest connectivity, to estimate forest modification. The way they defined modification means that only forests in the most remote and sparsely populated areas are scored as having high landscape integrity (see figure 2 and figure 4), although this was still ~40% of global forest area. They find 56% of protected forests have high landscape-level integrity (table 2). I agree with the authors that forest modification and degradation is important, but I don't think the authors made a good case that a) their findings are new / surprising, or that b) just mapping proximity to people is a great way to estimate ecological degradation let alone prioritize conservation action. It's true that being farther from people is generally helpful to forests, but the flip side is that this paper heavily devalues the natural areas that people most appreciate for recreation and ecosystem services, even though with high ecological function. It also ignores the contribution people can make to good stewardship and management.

Guadagno et al. 2021 is an an excellent new report from the Wildlife Conservation Society (as part of the Failure Factors Initiative) looking at the experience of conservation NGOs with using “pause and reflect” sessions to learn from failure (and success). Here are my key take-aways:

• People are reticent to talk publicly about failure for fear of losing respect, status and support for their work.
• Documenting “lessons learned” in reports is not as important as staff going through the process of talking together and informally learning from each other.
• Regularly reflecting on both what is working well and what could be improved (even for minor things, and for both successes and failures) makes teams better equipped to respond to serious or major failures (see Example 4 on p14). Having already built both trust and familiarity with a healthy way to learn from failure is excellent preparation when crises arise, allowing the group to work together to pivot effectively. These sessions don't have to take much time.
• Those regular reflections work best when there is high psychological safety (be respectful, focus on what happened and what to do next time and not who is to blame, recognize and address bias) and they are structured around a few core questions (what did we expect to happen vs. what happened, what went well and why, what can be improved and how). See page 21-25 for recommendations on how to do this, as well as guides / questions you can use.
• Sometimes a failure looks like a success at first, and in these reflections you can look for other explanations for apparent success (as per Example 1 on p7) allowing you to identify hidden problems and resolve them.
• Other times, a failure is at least partially a success, and these sessions can also identify some aspects of work going well even when we don’t achieve the outcomes we hoped for (see Example 2 on p11). Also even successes can probably be improved! (see Example 3 on p13).

The 2021 IPCC report had a lot of useful information! https://www.ipcc.ch/report/ar6/wg1/ Don't feel like reading 1,800 pages or even the 90 page summary or 215 page FAQ? Check out the 2 page 'headline statements' here:  https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Headline_Statements.pdf
The one thing to highlight for me is that limiting warming to 1.5C is now harder but not impossible (requiring net zero by 2055 w/ 90% gross emissions reductions). Current policies agreed to under Paris would still lead to 3C warming by 2100. One finding that I read about in this New York Times article (https://www.nytimes.com/2021/08/09/climate/climate-change-report-ipcc-un.html) really struck me: a bad heat wave that used to happen every ~50 years is now happening every ~10 years, and will happen every ~5 years at 1.5C or nearly annually at 4C. Don't miss this interactive tool to explore the results (and note you can download spatial data via the "share" icon): https://interactive-atlas.ipcc.ch/

Jenkins et al. 2015 highlights an inconvenient truth about protected areas in the United States: they are mostly located in places with relatively low species richness and threats of conversion. In other words, if the main goal of protected areas is to prevent as many species as possible from going extinct, they're poorly sited. You can compare biodiversity maps in Fig 1 & 2 to PAs in Fig 3 to see the mismatch. Fig 4 has their recommendations for 9 areas where conservation should be focused in the SE and West coast.

The findings of Leal et al. 2020 may seem obvious, but they're important to highlight: conservation planning focused on terrestrial species only does a poor job at protecting freshwater biodiversity. They did some modeling in Brazil to look at trade-offs between freshwater and terrestrial species, and how to improve planning. Their low-bar recommendation is that even without data on freshwater biodiversity, just considering aquatic connectivity in additional to terrestrial species roughly doubles the benefit to freshwater species with almost no decrease in terrestrial benefits (Fig 3e & 3f, purple lines). If planning considers both terrestrial and freshwater biodiversity data, about a 5% decrease in terrestrial benefits leads to a ~400% increase in freshwater benefits (Fig 3e & 3f, aqua lines). This represents a strong case against assuming terrestrial work will do a good job at protecting freshwater ecosystems, and the idea of just including aquatic connectivity is an appealing entry point in places where better freshwater data are unavailable.

LeFlore et al. 2021 looks at factors that tend to result in research being used via a focus on 40 small-scale conservation research projects on the Salish Sea. They found having a government collaborator was key, as was stakeholder engagement throughout the process, and that publishing a journal article didn't increase the chances of the research being used to inform decision-making. The impact bit was self-reported so I was pretty surprised only 40% of the projects were reported as leading to impact! It's hard to know how generalizable their results are, but I think it's fair to ask researchers to compare the time it takes to substantially engage w/ decision makers and other stakeholders, compare that to the time needed to publish, and to reflect on which is a higher priority use of their time. Full disclosure: I was a peer-reviewer of this paper.

Pressey et al. 2021 is an opinion piece arguing that conservationists need to shift focus from area-based protection targets (even those including representation) to avoided biodiversity loss (species extinction and habitat destruction) and ecological recovery. They make a fair and important point: despite increasing protection, the overall global trend of species and habitat loss is accelerating. So protected areas aren't working effectively (whether they're not managed well, or in the wrong places, or there aren't enough of them, or a mix). That's hard to argue with, and it's key that we find a way to better mitigate acute threats. But they lose me when they call for a lot more modeling of counterfactuals and monitoring of outcomes relative to the modeling. I've done that modeling, and it's slow, expensive, and subject to lots of assumptions and uncertainty. So rather than shifting lots of implementation dollars to more science, I'd favor using 'just enough' science to identify key needs for conservation, push advocacy to focus more on those needs than is currently happening, and do more spot monitoring to check efficacy and adapt.

Waldron et al. 2020 looks at global financial implications of 30 x 30 (6 terrestrial and 5 marine scenarios), and for tropical forests & mangroves adds in avoided costs and non-monetary ecosystem service values. They estimate that expanding protected areas (PAs) to 30% could result in increased direct global revenues of $64-454 billion / yr (depending on the scenario chosen, and mostly driven by increased nature tourism, see Table 3) as well as more food and wood production. Broader economic benefits (largely from avoided storm damage) could be $170-534 billion / yr more. With a estimated cost of $103-$178 billion / yr (which includes funding to manage existing PAs), they find net economic benefits to 30x30 across all scenarios (spend some time with Table 3 to see the details, but $235 billion / yr is the lowest net financial benefit). It's hard to vet this kind of complex analysis with a ton of assumptions. My gut tells me this is a pretty optimistic assessment due to several key assumptions (like a social cost of carbon at $135-540 / t CO2e , assuming big tourism increases and scarcity of wood driving up forest product revenue, etc.). But they point out that it could be an underestimate since they didn't include broader benefits of other ecosystems like grasslands. Note that other scientists criticized the Waldron paper, noting that not nearly enough has been done to estimate how 30x30 would affect people (nor to consult with them), among other issues. The critique (Agrawal et al. 2020) is here: https://openlettertowaldronetal.wordpress.com/

Welsby et al. 2021 ask an interesting question: what fraction of economically viable fossil fuels need to left in the ground to give us a 50% shot at limiting warming to 1.5C? The answer is pretty stark: by 2050 we need to leave 58% of oil, 59% of methane gas, and 89% of coal underground (a 3% annual reduction in oil and gas). See table 1 for their estimates by region. They note that we may need to leave even more fuels unextracted given questions about how fast we can develop "negative emissions" technology (carbon capture and storage).

As a number of NGOs look to invest in reforestation and forest protection as part of the solution to climate change, Williams et al. 2021 has a very important caveat. They found that while forests cool the earth by sequestering and storing carbon, they can also warm the earth in some cases by absorbing more heat than bare ground or snow would. So some forest loss in the U.S. (lower 48 where they did their modeling) has led to net cooling, even though overall it has led to warming. The cooling mostly happened in the Western US where there’s a lot of snow cover and the arid conditions make for light-color, reflective soils (so losing trees results in less local heat absorption). This paper is more pessimistic than the others I’ve read about temperate forests (for example Li et al. 2015 used remote sensing to actually measure temperature changes and compare nearby pixels with forest vs. open land cover) and finds that 15 years of forest loss only caused warming equal to 17% of a U.S. annual fossil fuel emissions (because the most forest loss has happened in Western states with lots of snow cover, balancing out more moderate forest loss elsewhere). Other work on this topic has found that boreal forests are the most likely to cause net warming (as per Mykleby et al. 2017), but for tropical forest accounting for evapotranspiration and albedo actually enhances their net cooling effect.


REFERENCES:
Barnes, M. D., Glew, L., Wyborn, C., & Craigie, I. D. (2018). Prevent perverse outcomes from global protected area policy. Nature Ecology & Evolution, 2(5), 759–762. https://doi.org/10.1038/s41559-018-0501-y

Dieckmann, N. F., Gregory, R., Satterfield, T., Mayorga, M., & Slovic, P. (2021). Characterizing public perceptions of social and cultural impacts in policy decisions. Proceedings of the National Academy of Sciences, 118(24), e2020491118. https://doi.org/10.1073/pnas.2020491118

Dobrowski, S. Z., Littlefield, C. E., Lyons, D. S., Hollenberg, C., Carroll, C., Parks, S. A., Abatzoglou, J. T., Hegewisch, K., & Gage, J. (2021). Protected-area targets could be undermined by climate change-driven shifts in ecoregions and biomes. Communications Earth & Environment, 2(1), 198. https://doi.org/10.1038/s43247-021-00270-z

Ellis, E. C., Gauthier, N., Klein Goldewijk, K., Bliege Bird, R., Boivin, N., Díaz, S., Fuller, D. Q., Gill, J. L., Kaplan, J. O., Kingston, N., Locke, H., McMichael, C. N. H., Ranco, D., Rick, T. C., Shaw, M. R., Stephens, L., Svenning, J.-C., & Watson, J. E. M. (2021). People have shaped most of terrestrial nature for at least 12,000 years. Proceedings of the National Academy of Sciences, 118(17), e2023483118. https://doi.org/10.1073/pnas.2023483118

Evans, C. D., Peacock, M., Baird, A. J., Artz, R. R. E., Burden, A., Callaghan, N., Chapman, P. J., Cooper, H. M., Coyle, M., Craig, E., Cumming, A., Dixon, S., Gauci, V., Grayson, R. P., Helfter, C., Heppell, C. M., Holden, J., Jones, D. L., Kaduk, J., … Morrison, R. (2021). Overriding water table control on managed peatland greenhouse gas emissions. Nature. https://doi.org/10.1038/s41586-021-03523-1

Grantham, H. S., Duncan, A., Evans, T. D., Jones, K. R., Beyer, H. L., Schuster, R., Walston, J., Ray, J. C., Robinson, J. G., Callow, M., Clements, T., Costa, H. M., DeGemmis, A., Elsen, P. R., Ervin, J., Franco, P., Goldman, E., Goetz, S., Hansen, A., … Watson, J. E. M. (2020). Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity. Nature Communications, 11(1), 1–10. https://doi.org/10.1038/s41467-020-19493-3

IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu and B. Zhou (eds.)]. Cambridge University Press. In Press. https://www.ipcc.ch/report/ar6/wg1/

Jenkins, C. N., Van Houtan, K. S., Pimm, S. L., & Sexton, J. O. (2015). “US protected lands mismatch biodiversity priorities.” Proceedings of the National Academy of Sciences, 112(16), 5081–5086. https://doi.org/10.1073/pnas.1418034112

Leal, C. G., Lennox, G. D., Ferraz, S. F. B., Ferreira, J., Gardner, T. A., Thomson, J. R., Berenguer, E., Lees, A. C., Hughes, R. M., Mac Nally, R., Aragão, L. E. O. C., de Brito, J. G., Castello, L., Garrett, R. D., Hamada, N., Juen, L., Leitão, R. P., Louzada, J., Morello, T. F., … Barlow, J. (2020). Integrated terrestrial-freshwater planning doubles conservation of tropical aquatic species. Science, 370(6512), 117–121. https://doi.org/10.1126/science.aba7580

Guadagno, L., Vecchiarelli, B. M., Kretser, H., & Wilkie, D. (2021). Reflection and Learning from Failure in Conservation Organizations: A Report for the Failure Factors Initiative. https://doi.org/10.19121/2021.Report.40769

LeFlore, M., Bunn, D., Sebastian, P., & Gaydos, J. K. (2021). Improving the probability that small‐scale science will benefit conservation. Conservation Science and Practice, October. https://doi.org/10.1111/csp2.571

Pressey, R. L., Visconti, P., McKinnon, M. C., Gurney, G. G., Barnes, M. D., Glew, L., & Maron, M. (2021). The mismeasure of conservation. Trends in Ecology & Evolution, 36(9), 808–821. https://doi.org/10.1016/j.tree.2021.06.008

Waldron, A., Adams, V., Allan, J., Arnell, A., Asner, G., Atkinson, S., Baccini, A., Baillie, J. E., Balmford, A., Austin Beau, J., Brander, L., Brondizio, E., Bruner, A., Burgess, N., Burkart, K., Butchart, S., Button, R., Carrasco, R., Cheung, W., … Zhang, Y. (2020). Protecting 30% of the planet for nature: costs, benefits and economic implications.

Welsby, D., Price, J., Pye, S., & Ekins, P. (2021). Unextractable fossil fuels in a 1.5 °C world. Nature, 597(7875), 230–234. https://doi.org/10.1038/s41586-021-03821-8

Williams, C. A., Gu, H., & Jiao, T. (2021). Climate impacts of U.S. forest loss span net warming to net cooling. Science Advances, 7(7), 1–7. https://doi.org/10.1126/sciadv.aax8859


Sincerely,
 
Jon