May 2025 science summary

Merry May,

This month I've got four articles on freshwater, plus one on whether climate mitigation can be harmful to wildlife if done wrong (spoiler: yup).

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon (no need to email me).

FRESHWATER:
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.

Lehner et al. 2024 is a summary of a new "Global Dam Watch (GDW)" open dataset of 41,000 river barriers and 35,000 reservoirs (see Fig 1 for a map). While national and regional datasets are more complete (e.g., NID has 90k points in the US, AMBER has 630k in Europe), this is the most comprehensive free global dataset (see Table 2) and it includes estimated reservoir volumes mostly for reservoirs >10 km2.

Cho et al. 2023 did a ton of modeling (Fig 7) to estimate how conservation (mostly reforestation along streams) could have affected the water supply of São Paulo. They found the increased habitat could serve as an "invisible reservoir" for water in soil, and in a highly idealized scenario (lots of new forest in all the right places among others) streamflow could be boosted by 33% (and drought costs reduced by 28%). They don't report numeric results for their less ideal scenarios, and all scenarios exclude the water consumption of growing trees. In a conversation with one of the study's authors, they mentioned that it likely took about 30 years (I think) for the "water savings" of nature (fog capture plus slowing down runoff during high rain events) to outweigh the water consumption of growing trees. In other words, in this case in the short term adding trees could result in lower streamflow even though in the long run it would increase streamflow. Understanding the timeline and tradeoffs is key so people who live there know what to expect. From chatting w/ other hydrologists about this, it's clear that results like this vary a lot depending on things like soil type, weather and climate, type of forest, and much more. There's an article about this one at https://www.nature.org/en-us/about-us/where-we-work/latin-america/brazil/stories-in-brazil/invisible-reservoir/

Pompeu 2025 quantitatively models how different drivers have impacted total water surface area (as a decent proxy for total flow / water quantity) in the Pantanal. The paper found the biggest driver of water level was 1) the presence or absence of having natural vegetation at least 50m around springs, followed by 2) natural veg riparian buffers along rivers (buffer width increasing w/ river width as per the Forest Code), followed by 3) replacing conventional monoculture ag w/ something w/ deeper root systems (agroforestry, permaculture, full restoration if feasible, etc.), followed by 4) preventing more dams.


CLIMATE MITIGATION AND WILDLIFE:
Smith et al. 2025 asks what the net impact of climate mitigation on land (including bioenergy crops, reforestation, and afforestation) is on the total habitat area for 14,000 vertebrate species. Fig 1 summarizes the idea well - climate change can reduce suitable habitat, but climate mitigation can also either add or remove habitat directly. Fig 4 has their global recommendations - basically leave most ecosystems alone, reforest several areas (SE Asia, Eastern US, Mexico, and much of Europe) and in a few tiny places grow bioenergy crops. In other words, typically planting trees on grasslands or other habitat types destroys more habitat than it saves through climate mitigation. But planting trees in cleared forests is a win-win.


REFERENCES:
Cho, S. J., Klemz, C., Barreto, S., Raepple, J., Bracale, H., Acosta, E. A., Rogéliz-Prada, C. A., & Ciasca, B. S. (2023). Collaborative Watershed Modeling as Stakeholder Engagement Tool for Science-Based Water Policy Assessment in São Paulo, Brazil. Water, 15(3), 401. https://doi.org/10.3390/w15030401

Lehner, B., Beames, P., Mulligan, M., Zarfl, C., De Felice, L., van Soesbergen, A., Thieme, M., Garcia de Leaniz, C., Anand, M., Belletti, B., Brauman, K. A., Januchowski-Hartley, S. R., Lyon, K., Mandle, L., Mazany-Wright, N., Messager, M. L., Pavelsky, T., Pekel, J.-F., Wang, J., … Higgins, J. (2024). The Global Dam Watch database of river barrier and reservoir information for large-scale applications. Scientific Data, 11(1), 1069. https://doi.org/10.1038/s41597-024-03752-9

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

Pompeu, J. (2025). Cross-Boundary Drivers of Water Cover Reduction in the Pantanal Wetland and Implications for its Conservation. Wetlands, 45(3), 32. https://doi.org/10.1007/s13157-025-01916-w

Smith, J. R., Beaury, E. M., Cook-Patton, S. C., & Levine, J. M. (2025). Variable impacts of land-based climate mitigation on habitat area for vertebrate diversity. Science, 387(6732), 420–425. https://doi.org/10.1126/science.adm9485


Sincerely,
 
Jon

p.s. This is a sea lion lazing about in Valdivia who happened to yawn as I was watching them.

November 2024 science summary

Howdy,

I've got summaries of articles on carbon credits, wetlands and climate mitigation, and the Pantanal (drought, fire, and habitat loss).

But first - two quick notes on the use of artificial intelligence (AI):

1. When I mention AI tools I should say this every time: a) assume that any information you put into an AI may be shared in ways you don't want, so never put in sensitive / non-public information. b) that also means be wary of putting in copyrighted materials! Some publishers like Elsevier and New York Times have a blanket ban on using their publications in AI tools, and others allow some uses but not others!
2. I'm continuing to find Elicit a really helpful tool to find and summarize or extract info from science papers. If you have questions or want to chat about it let me know. If you register for a free account I can send you links to my custom notebooks to show how some cool features work.

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon (no need to email me).

CARBON CREDITS
Trencher et al, 2024 is an analysis of the quality of credits on the voluntary carbon market. They focus on the 20 companies retiring the most credits between 2020-2023 (134 million metric tons CO2e), which is 20% of all global retirements on the three registries (see Fig 1 for company list). They found 87% of credits have a high risk of not providing real additional reductions (6% were low risk, most of the rest was medium), and 97% of credits focused on avoiding emissions rather than removal. Note that they classified all REDD+ (reducing deforestation and/or degradation) as high risk given that they have often 1) overestimated additionality, 2) not stopped deforestation, and/or 3) displaced deforestation elsewhere (aka 'leakage'). They also classify large-scale renewable energy as high-risk, since the price of credits is not typically the decisive factor in those projects (they are often built w/ or w/o credits) and they are often build in countries w strong government support for renewable energy. They also found that companies strongly prefer the cheapest credits (which creates demand for lower-quality offsets) often from older projects, although some companies have paid a lot more for REDD projects. The authors call for more regulation of the voluntary market, and for companies not using voluntary credits to support claims of offsetting emissions.

Blanchard et al. 2024 is a short opinion piece arguing that to fund nature conservation, we should pivot from an "offset" model (where companies buy credits to support assertions of lower net emissions and/or being carbon neutral) to a "contributions" model (where the financial contributions are recognized, but not taken as equivalent to reducing gross emissions). The authors say that 1) all entities should prioritize their own direct emissions reduction before seeking to pay others to do that, 2) we need to use the best science to pick what investments are most likely to lead to durable climate mitigation (considering reversibility, other GHGs, albedo, etc.), and 3) independent scientists should audit any quantitative claims made about the benefits of contributions to climate mitigation.


WETLANDS AND CLIMATE CHANGE MITIGATION
Arias-Ortiz et al. 2024 estimate how much methane different kinds of marshes in the U.S. emit each year. They found that warm freshwater marshes (>25.6C mean annual high temperature) produce the most methane by far (172 g CH4/m2/yr = 48.2 t CO2e / yr), followed by other freshwater marshes at low or medium elevation (producing ~1/3 that on average). Across all marshes the average is much lower (26 g CH4/m2/yr = 7.3 t CO2e / yr), and saltier marshes emit less methane. They report mangroves emit roughly twice as much methane flux as marshes, but seagrasses only emit 10% as much as marshes. Predicted methane was really close to measured methane (at least once they calibrated their estimates)


PANTANAL:
Marengo et al. 2021 is a review of the severe drought in the Pantanal in 2019 and 2020. The key direct cause was less warm humid air coming from Amazonia leading to much less rain across the Paraguay river basin, which in turn led to very low water levels in rivers and other wetlands, which reduced shipping goods by river (and economic losses) and enabled widespread fires. Previous studies looking at Pantanal rainfall trends have found only a small overall decrease but with a lot more variation each year. There are more days with no rain, the dry season has gotten drier, the Ládario river has been dropping ~3 cm / yr for 30 years, but the flooding in 2018 was unusually extensive. Part of the issue may be that the Pantanal has been relatively wet since roughly 1970, making a return to severe droughts that have not been seen for decades feel more unusual (see Fig 3). El Niño does not seem to be a driver of drought, nor do various climatic indices correlate well w/ drought years. But in 2019-2020 a strong South Atlantic Convergence Zone caused a shift in dominant winds to the Pantanal coming from drier and colder higher-latitude air.

Guerra et al. 2020 looked at the drivers of predicted habitat conversion in the Upper Paraguay River Basin (including the Pantanal, some of the Cerrado, and a bit of the Amazon) between 2008-2016 (broken into four 2-year periods). Key drivers in the Pantanal were unprotected status and existing land cover, with much weaker impact from elevation (higher means more loss), and in half the time periods there was also an influence of distance to roads (closer means more loss) and cattle (presence leading to more loss). Oddly there was LESS conversion near annual cropland which is very unusual except in dense fully converted ag landscapes. They only saw more habitat loss on land with good ag potential near rivers in the Pantanal from 2010-2012, which could be related to cropland moving closer to water due to the 2012 drought. Note that this model assumes deforestation expands from where it has already happened, rather than modeling other factors (economic, population modeling, commodity prices, planned roads, etc.) to look for what might change in the future.

Martins et al. 2024 recommend priority areas for fire prevention and/or restoration in the Upper Paraguay River Basin, based on the number of fire-sensitive species present (along w/ factors like fire frequency and intensity, dry biomass, and time since the last burn). The relatively few top priority areas for fire management are in red on Fig 2, and occur in a triangle roughly between Paiaguás, Aquidauana, and Bodoquena. There are many more areas flagged as a priority for restoration, but their top focus is 1,206 km2 of forest high in both resilience and sensitive species. But they also note ~6,000 km2 of potential restoration priorities that hadn't been burnt until recently (2019-2022, Fig 5). The supplement also maps the most important places for fire prevention (Supplementary Fig 15).


REFERENCES:

Arias-Ortiz, A., Wolfe, J., Bridgham, S. D., Knox, S., McNicol, G., Needelman, B. A., Shahan, J., Stuart-Haëntjens, E. J., Windham-Myers, L., Oikawa, P. Y., Baldocchi, D. D., Caplan, J. S., Capooci, M., Czapla, K. M., Derby, R. K., Diefenderfer, H. L., Forbrich, I., Groseclose, G., Keller, J. K., … Holmquist, J. R. (2024). Methane fluxes in tidal marshes of the conterminous United States. Global Change Biology, 30(9). https://doi.org/10.1111/gcb.17462

Blanchard, L., Haya, B. K., Anderson, C., Badgley, G., Cullenward, D., Gao, P., Goulden, M. L., Holm, J. A., Novick, K. A., Trugman, A. T., Wang, J. A., Williams, C. A., Wu, C., Yang, L., & Anderegg, W. R. L. (2024). Funding forests’ climate potential without carbon offsets. One Earth, 7(7), 1147–1150. https://doi.org/10.1016/j.oneear.2024.06.006

Guerra, A., Roque, F. de O., Garcia, L. C., Ochao-Quintero, J. M. O., Oliveira, P. T. S. de, Guariento, R. D., & Rosa, I. M. D. (2020). Drivers and projections of vegetation loss in the Pantanal and surrounding ecosystems. Land Use Policy, 91(April 2020). https://doi.org/10.1016/j.landusepol.2019.104388

Martins, P. I., Belém, L. B. C., Peluso, L. M., Szabo, J. K., Trindade, W. C. F., Pott, A., Junior, G. A. D., Jimenez, D., Marques, R., Peterson, A. T., Libonati, R., & Garcia, L. C. (2024). Fire-sensitive and threatened plants in the Upper Paraguay River Basin, Brazil: Identifying priority areas for Integrated Fire Management and ecological restoration. Ecological Engineering, 209(1), 107411. https://doi.org/10.1016/j.ecoleng.2024.107411

Marengo, J. A., Cunha, A. P., Cuartas, L. A., Deusdará Leal, K. R., Broedel, E., Seluchi, M. E., Michelin, C. M., De Praga Baião, C. F., Chuchón Angulo, E., Almeida, E. K., Kazmierczak, M. L., Mateus, N. P. A., Silva, R. C., & Bender, F. (2021). Extreme Drought in the Brazilian Pantanal in 2019–2020: Characterization, Causes, and Impacts. Frontiers in Water, 3(February). https://doi.org/10.3389/frwa.2021.639204

Trencher, G., Nick, S., Carlson, J., & Johnson, M. (2024). Demand for low-quality offsets by major companies undermines climate integrity of the voluntary carbon market. Nature Communications, 15(1), 6863. https://doi.org/10.1038/s41467-024-51151-w

Sincerely,
 
Jon
 
p.s. these are jack o' lantern vegan quesadillas from our Halloween party