Wednesday, November 1, 2023

October 2023 science summary

Jon and Kong napping on the couch

Hello again,

This month I review papers on inequitable restoration, the carbon impact of working from home, learning from failure, and connectivity. I also have some notes on using AI to help with your lit review. And a shameless plug for our foster dog (Kong) pictured above.

Kong is a an exuberant dog ready to bring some joy to someone’s life! He is a great partner for the dog park, hiking, playing ball in the yard, and lots and lots of cuddling. He has so much love to give, and likes every person and dog he meets.  He would enjoy a playful dog brother or sister, and gets along well with cats and kids. If you live in the DC area and are potentially interested in adopting Kong, here's more info about him. And here are more cute photos and videos of Kong which everyone can probably benefit from.

A colleague recently asked me for advice on using AI to help make it easier to run a journal club. She wanted help narrowing down which papers to read and recommend to the group. My favorite tool for this purpose is still elicit (, which I reviewed in my March 2023 summary). Just upload a folder of manuscript PDFs, be sure to turn on the "detailed summary" field (the default summary leaves out enough to be misleading), and review the spreadsheet of summaries you get. It's a great way to pick which articles to start with and which to condemn to the "maybe eventually I'll read this but who am I kidding" folder unless something changes. 

Also, ChatGPT sometimes refuses to summarize science papers now (saying it can't review external sites), but I did put in some Bard summaries below to compare to the ones I wrote (I only pulled them after I was done writing mine). Bard rolled out a feature in September where you can sometimes check its sources (since it still is prone to getting facts wrong), but in recent testing there was no text available for me to easily check with their tool.

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

Jon summary:
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.

Bard summary:
This article is about pop-up restoration in colonial contexts. It discusses the problems with pop-up restoration, which is restoration that is done without Indigenous input and does not consider Indigenous knowledge. The authors argue that pop-up restoration can actually do more harm than good. They propose that instead, restoration should be done in collaboration with Indigenous communities and should center Indigenous knowledge.

Jon summary:
Tao et al. 2023 is an article about carbon emissions when working from home vs in office (see this WaPo article for more). They claim in the abstract remote workers can have a 58% lower carbon footprint than staff fully in the office, BUT there are a bunch of issues with the paper that make me think this claim is invalid (although I'm almost certain there are carbon benefits). First - the 58% number in the abstract does not appear anywhere in the paper (even the SI), the results say 54%. It's a small difference but seems sloppy which can be a warning sign. Next, the methods (even in the SI) do not really explain their calculations in full. They do not define the components of "office energy use" let alone how they measure and calculate it, which is bewildering (they seem to have modeled how attendance & headcount related to office actual energy use but that's about all I could figure out). As a result I can't assess the amount of energy related to occupancy vs. not (I presume heating and cooling are not affected unless there's enough remote workers to shrink the office building). Finally, two assumptions seem especially problematic. First is that residential heating, cooling, and (de)humidifying is OFF when staff are not at home. That is pretty rare for people who live in places w/ hot summers and/or cold winters. Second, the benefits they cite only come from seat sharing, not just people working at home and leaving their seat empty. That's a valid scenario to look at, but it undercuts the framing about benefits from working from home X days per week (and note that many offices want staff to be in on the same days, rather than rotate, which limits seat sharing). So I'm not convinced on their office energy estimates, but the avoided carbon from having fewer commutes is hard to argue with. The authors argue that people working remotely have more NON-commute travel though, so savings are less than you'd think. So let's keep talking about benefits of remote and hybrid work, but NOT assume that will dramatically shrink our carbon footprint of work.

Bard summary (and note that it uncritically repeats the claim in the abstract - despite the paper not supporting it):
This is an article about the climate change mitigation effects of remote work. It discusses the environmental impacts of commuting, non-commute travel, office energy use, and residential energy use. Remote work can reduce up to 58% of the carbon footprint of work. The impacts of IT usage are negligible. The environmental benefits of remote work depend on proper configuration of lifestyle and workplace.

Jon summary:
Hanson et al. 2023 compares 8 approaches to optimally expand protected areas (PAs) for birds in Washington state that all consider connectivity differently (all spending $7.6 billion). Some are oblique (maximizing total protected area and presuming it will decrease mean distance between habitat), some focused on connectivity WITHIN PAs (minimizing edge / perimeter, which likely REDUCES connectivity between PAs so looks very different), and several with different assumptions about what conditions facilitate the most species movement (like focusing on connecting areas w/ relatively homogeneous cores and corridors). See Table 2 for pros and cons of each approach, and Fig 2 for maps comparing the results (blue is unique to that approach, yellow was included by all, orange was shared by at least two). There was no obvious winner, but the 'environmental similarity' approach scored pretty well on most. Note that land cost is a big driver of the results.

For this one Bard said "I'm a text-based AI and can't assist with that." (or variants on this reply when I tried again). Seems to be an access issue since it still worked for the other articles here.

Jon summary:
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, that is likely time well spent given that how often an insufficient ToC was listed as a cause of failure.

Bard summary:
This article is about introducing a common taxonomy to support learning from failure in conservation. It discusses the need for a culture shift in conservation towards learning from failure. It also details the development of a taxonomy of root causes of failure in conservation. The taxonomy is organized into three tiers: overarching cause categories, midlevel cause categories, and specific root causes. The authors tested the taxonomy by asking conservation practitioners to use it to classify the causes of failure for conservation efforts they had been involved in. The authors then analyzed the frequency that particular root causes were encountered by projects within this test sample. The authors suggest that the taxonomy could be used to improve the identification, analysis, and subsequent learning from failed conservation efforts.

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.

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.

Hanson, J. O., Vincent, J., Schuster, R., Fahrig, L., Brennan, A., Martin, A. E., Hughes, J. S., Pither, R., & Bennett, J. R. (2022). A comparison of approaches for including connectivity in systematic conservation planning. Journal of Applied Ecology, 59(10), 2507–2519.

Tao, Y., Yang, L., Jaffe, S., Amini, F., Bergen, P., Hecht, B., & You, F. (2023). Climate mitigation potentials of teleworking are sensitive to changes in lifestyle and workplace rather than ICT usage. Proceedings of the National Academy of Sciences, 120(39), 2017.


p.s. In the photo above, Kong is sleeping with his head on my lap, while I am resting my head on him. He is such a sweet and cuddly dog.

Tuesday, October 24, 2023

September 2023 science summary

Giant anteater


This month I have just two articles - one on conservation priorities (a longer than usual review) and one on how mining affects tropical rivers. I also forgot to post on this site for a few weeks, sorry!

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

Mair et al. 2021 proposes the use of a "species threat abatement and restoration (STAR)" metric with two scores. The threat abatement one for a location (START) sums up each threatened species present, with higher threat like Critically Endangered scoring higher, favoring locations with more species that are more threatened. The idea is to estimate effort to abate all threats (which seems unreasonable). The restoration score (STARR) divides 'restorable habitat' for all threatened species in a given pixel by global habitat for that species, and sums across species.

The paper calculates both for threatened terrestrial vertebrates. START results look pretty similar to range-size rarity scores for threatened species or a few other existing metrics, and suffer from the same issues (bias to data-rich places, lack of accurate info in many places). STARR seems more conceptually interesting but I'm pretty suspicious that the projected range maps are valid (given issues w/ current range maps) and since they didn't screen out any low-feasibility areas (like highly productive ag) it doesn't seem too useful. I also struggle to understand how they could have come up with the map in Fig 2b using the methods they describe. But that could be me being slow rather than a problem with the analysis.

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.

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.

Mair, L., Bennun, L. A., Brooks, T. M., Butchart, S. H. M., Bolam, F. C., Burgess, N. D., Ekstrom, J. M. M., Milner-Gulland, E. J., Hoffmann, M., Ma, K., Macfarlane, N. B. W., Raimondo, D. C., Rodrigues, A. S. L., Shen, X., Strassburg, B. B. N., Beatty, C. R., Gómez-Creutzberg, C., Iribarrem, A., Irmadhiany, M., … McGowan, P. J. K. (2021). A metric for spatially explicit contributions to science-based species targets. Nature Ecology & Evolution, 5(6), 836–844.

Walmsley, B. (2023). Satellite images show the widespread impact of mining on tropical rivers. Nature, 620(7975), 729–730.

p.s. This is a photo of a giant anteater that I saw on a recent trip to the Pantanal in Brazil. If you're curious I have more Pantanal photos and Pantanal videos.

Tuesday, August 1, 2023

August 2023 science summary

Cardinal on blueberry cage


I'm behind on science reading again but still have three articles to share. Two are on wildlife migrations, and one is on bullshit (really)!

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

Turpin et al 2021 finds that being able to produce satisfying and seemingly accurate bullshit ("communication characterised by an intent to be convincing or impressive without concern for truth") seems correlated with real intelligence (albeit using weak proxies of a 10-item vocabulary test, and ratings of how others perceived their intelligence from writing samples). See Fig 1 for how they rated how convincing bullshit was. Interestingly people who scored better on the vocab test were slightly less willing to bullshit, and people more willing to bullshit were less able to distinguish bullshit from meaningful info. So a TL;DR could be that smarter people are less susceptible to bullshit, less willing to bullshit, but also better at bullshitting convincingly. Hat tip to Patrick Beary for sending this. And in case you're thinking this is a one-off joke, another paper on bullshit I reviewed ("On the reception and detection of pseudo-profound bullshit") has 597 citations!

Remember the 'lockdown' in the early days of COVID where people were asked to stay at home as much as possible, and traffic and even people walking around plummeted? Tucker et al. 2023 looks at how that impacted 43 species of mammals around the world. They found it varied a ton, but that in the short term (hour to hour) animals moved a bit less (presumably from less trying to avoid people). They found longer-term movement (10-day distance) only changed for coutnries with the strictest lockdowns like Italy and France, and Fig 3a makes it clear that while that change is significant it's dwarfed by the variation in effect. The findings on roads are not significant at the individual level and the effects they're reporting don't seem very compelling so I'm leaving those out. There's a Washington Post article about this paper here which includes some stories about some of the more adventurous animals:

Young et al. 2023 monitored wildlife crossings along the Toowoomba Bypass in eastern Australia and found they were mostly used by non-native animals like feral cats, European redfoxes, and European hares (as well as dingoes). They also compared wildlife presence and density to adjacent bushland; only 61% of all the species they found were detected at crossings at all. The only difference they saw between viaducts, culverts, and underpasses was that swamp wallabies and hares both preferred the viaduct.


Tucker, M. A., Schipper, A. M., Adams, T. S. F., Attias, N., Avgar, T., Babic, N. L., Barker, K. J., Bastille-Rousseau, G., Behr, D. M., Belant, J. L., Beyer, D. E., Blaum, N., Blount, J. D., Bockmühl, D., Pires Boulhosa, R. L., Brown, M. B., Buuveibaatar, B., Cagnacci, F., Calabrese, J. M., … Mueller, T. (2023). Behavioral responses of terrestrial mammals to COVID-19 lockdowns. Science, 380(6649), 1059–1064.

Turpin, M. H., Kara-Yakoubian, M., Walker, A. C., Walker, H. E. K., Fugelsang, J. A., & Stolz, J. A. (2021). Bullshit Ability as an Honest Signal of Intelligence. Evolutionary Psychology, 19(2), 1–10.

Young, G., King, R., & Allen, B. L. (2023). Where do wildlife cross the road? Experimental evaluation reveals fauna preferences for multiple types of crossing structures. Global Ecology and Conservation, e02570.

p.s. After the birds ate every single blueberry I grew last year, I built a cage this year w/ gaps big enough to let some pollinators in but keep birds out (until we harvested enough and let them have the last of them). They periodically would check for gaps, and twice robins managed to squeeze in and get stuck until I let them out. I'll improve the design next year.

Monday, July 3, 2023

July 2023 science summary

Little mermaid food 

This month I have two articles on climate resilience, one on climate mitigation, and one on science-implementation partnerships. Plus a couple articles on AI as usual.

While it's a Canadian science fair project and not peer-reviewed science, I was interested to see this test of "you catch more flies with honey than vinegar." The experiment found that you catch more flies with honey and vinegar than with vinegar alone, which catches more than honey alone. But bringing it back to the saying: please don't be a jerk regardless.

My obligatory article on AI (and specifically Large Language Models [LLMs] like ChatGPT) is extra-fascinating this month. Can (and should) LLMs help us communicate more empathically? Check out this NY times article 'When Doctors Use a Chatbot to Improve Their Bedside Manner.' I love the idea of someone wanting to be kind by using the right words, not knowing what to say, and getting help with that. I have found it's very common for people to stay silent when they can't find 'the right words' around illness and death and grief, so I am all for helping people (including doctors) to get unstuck. I asked Bard (Google's LLM) for advice on how to support a friend who is grieving and found it mostly excellent. Not ideal but really good and something most of us could learn from. The idea of machines helping us to express empathy more effectively is so intriguing and I'm all for it.

The latest AI tool I tried out is "ChatPDF" which lets you upload a PDF and ask the tool questions about it. It works pretty well for some things, but is oddly dull in others. Like for one paper I asked it which species was responsible for most of the primary effect they reported (t CO2e of climate mitigation) and it didn't know. But when I asked it what the contribution was of the species I knew drove >80% of the effect, it reported it numerically. Apparently it was unable to divide the number it knew for the species in question by the total effect size number (which it also knew). But I thought it performed reasonably well with my questions about the IPCC report. TL;DR is that it seems better at finding / extracting info than any kind of reasoning.

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

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).

Anderson et al. 2023 is the latest paper supporting the data in The Nature Conservancy's Resilient Land Mapping Tool ( They looked for overlap in three layers across the US: biodiversity value (the union of TNC's ecoregional priority areas), resilient sites (places with diverse and connected microclimates), and 'climate flow' (a circuit theory analysis of where wildlife is likely to shift in response to climate change). See Fig 1 for their main results, or the web map is better since you can separate out the three main layers. The way 'biodiversity value' was assessed varies a lot by ecoregion, and some are more ambitious than others (e.g., the biggest biodiversity patch is in the Nebraska Sandhills, but other ecoregions also have some big blocks of intact habitat). So not every green blob is equally high-priority, but collectively it does have representation across all ecoregions which is good. On the main map, both blue and dark green blobs offer the most value for climate resilience, but again the web map lets you see the continuous data.

Rubenstein et al. 2023 is a systematic review of how documented range shifts (by plants and animals, 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. 

Carter et al. 2020 is a call for better coordination of science across landscapes in the Western US to better inform land management. They walk through 5 examples of how it has worked (standard monitoring for national parks, tools to help restore arid & semi-arid landscapes, predictive soil maps of where reclaiming disturbed land could work, frameworks for sage-grouse monitoring, and targeted interventions to improve big-game connectivity). They ask agencies to better support boundary-spanning partnerships w/ scientists, and to make more specific asks to scientists about what information they need. I'm not convinced that's likely; White et al. 2019 and others have found land managers don't always see science as a key input, they're often too busy to even know where they need help, and a high-engagement partnership may not always be the best pitch to agency staff who are stretched thin.

Anderson, M. G., Clark, M., Olivero, A. P., Barnett, A. R., Hall, K. R., Cornett, M. W., Ahlering, M., Schindel, M., Unnasch, B., Schloss, C., & Cameron, D. R. (2023). A resilient and connected network of sites to sustain biodiversity under a changing climate. Proceedings of the National Academy of Sciences, 120(7), 1–9.

Carter, S. K., Pilliod, D. S., Haby, T., Prentice, K. L., Aldridge, C. L., Anderson, P. J., Bowen, Z. H., Bradford, J. B., Cushman, S. A., DeVivo, J. C., Duniway, M. C., Hathaway, R. S., Nelson, L., Schultz, C. A., Schuster, R. M., Trammell, E. J., & Weltzin, J. F. (2020). Bridging the research-management gap: landscape science in practice on public lands in the western United States. Landscape Ecology, 35(3), 545–560.

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.

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.


p.s. The photo is of food we made for a little mermaid party, including crab cupcakes (no crab in them, they were vegan), mermaid tail ice cream cones, sugar cookies, and veggie sushi 

Thursday, June 1, 2023

June 2023 science summary

Space pansies


I haven't had much time to read science this month, so I'm just sharing a newspaper article about AI training, and one science article along w/ alternative summaries of it to highlight Bing chat options.

This is a fascinating article about which web sites AI tools are trained on, and what that implies for their accuracy, bias, etc.
When I asked ChatGPT "What are the most critical weaknesses of ChatGPT" one answer was 'Bias in Training Data: The training data used to develop ChatGPT is sourced from the internet and can contain biases, inaccuracies, and offensive content. This can lead to the model reproducing and amplifying these biases in its responses.'

Another good read comes from the New York Times, with detail about how chatbots regularly completely fabricate untrue information (or 'hallucinate'). It's an important read if you ever ask chatbots for what you hope is factual information. How bad can the fabrications be? They have falsely accused people of sexual harassment and bribery, pointing to non-existent sources.

For those who haven't used it yet, Bing's version of ChatGPT has some nice features, namely 1) it provides actual references by default (the normal ChatGPT will provide references upon request, but they often don't have the info ChatGPT provided), 2) you can switch between 'creative' or 'precise' or 'balanced' response styles (I include examples below). To try it out, open Microsoft Edge (it won't work in other browsers), do a search on, and right below the search box click "Chat" to the right of "Search". Note that as per the article above, the references may still be false!

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

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.

Here's a Bing AI summary using the "precise" option  (99 words):
'The paper “Why facts don’t change minds: Insights from cognitive science for the improved communication of conservation research” discusses four common myths about how to best communicate science for decision-making. These myths are: that facts change minds, scientific literacy will lead to enhanced research uptake, individual attitude change will shift collective behaviors, and broad dissemination is best. The article provides four alternative insights that can support effective science communication and impact: engaging the social mind for optimal decision-making, understanding the power of values, emotions, and experience in swaying minds, changing collective behavior, and thinking strategically for biggest impact.'

Here's a Bing AI summary using "creative" (262 words):
'The article argues that conservation scientists need to update their models of science communication and behavioral change based on insights from cognitive science. It challenges four common myths about how to best communicate science for decision-making, and provides four alternative insights that can support effective science communication and impact. The myths and insights are:
•    Myth: Facts change minds. Insight: Engage the social mind for optimal decision-making. The article explains that humans are social animals who rely on their peers and trusted sources for information, and that facts alone are not enough to persuade people who have strong prior beliefs or identities.
•    Myth: Scientific literacy will lead to enhanced research uptake. Insight: Understand the power of values, emotions, and experience in swaying minds. The article shows that people tend to filter information based on their values, emotions, and personal experiences, and that scientific literacy does not necessarily lead to more rational or pro-environmental choices.
•    Myth: Individual attitude change will shift collective behaviors. Insight: Change collective behavior by targeting social norms and networks. The article suggests that individual attitudes are often influenced by social norms and networks, and that changing collective behavior requires understanding and leveraging these social factors.
•    Myth: Broad dissemination is best. Insight: Think strategically for biggest impact. The article advises that conservation scientists should be more strategic and selective in their communication efforts, and focus on the most relevant and influential audiences, messages, and channels.
The article concludes by calling for more interdisciplinary collaboration between conservation scientists and cognitive scientists to design and evaluate effective science communication interventions for conservation impact.'

Note I started w/ "balanced" but found it the least useful of the three so am skipping it here.

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.

 p.s. These 'space pansies' always make me think my elevated planter has somehow become sci-fi whenever I walk by

Monday, May 1, 2023

May 2023 science summary

Nut Case by Katie Hudnall


Does spring feel like it came early or late? It's not just you! DC leafed out 3 weeks ahead of schedule.

This month is a bit of a grab bag: three papers on fishery management, one on assisted migration for wildlife, one on forests & fire, and one on the role of wildlife in climate mitigation that I found pretty misleading.

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

Schmitz et al. 2023 makes a fair point but uses some egregious estimates to do so (please don't trust the estimated climate mitigation benefits). They argue that the role of animals in boosting carbon sequestration (and/or reducing soil carbon and methane emissions) in underappreciated, and they may be right. Fig 1 is a cool thought experiment looking at potential impacts of boosting animal populations in different case studies. BUT the estimate of a huge 6.41 additional Gt CO2e / yr that could be reduced via animals is based on some really weak assumptions. For example, 86% of that 6.41 Gt comes from marine fish (5.5 Gt / yr). But that 5.5 Gt comes from another report, and is actually an estimate of CURRENT fish carbon flux (not potential to increase additional sequestration via conservation) recognizing a ton of uncertainty. Their bison estimate (another 9% of the 6.41 Gt) assumes that bison start grazing ungrazed lands when in fact they'd be displacing cattle in most cases (and one of the papers they cite lists the C benefit of cattle and bison as about the same). The only other animal with a substantial contribution is grey wolves (4% of total), and it's based on a single study on net primary productivity in Michigan which ignores the albedo effect. So overall, this study starts with decent evidence but makes some really flawed assumptions about how to translate them into global climate mitigation potential.


Fitzpatrick et al. 2023 looks at the potential for assisted migration (moving individual animals to different habitats, sometimes along w/ targeted captive breeding) as a form of 'genetic rescue' to restore gene flow across fragmented federally listed vertebrate populations in the US via assisted migration. They gave 222 spp a score from -1->4, with 2/3 of spp scoring 2 or higher (and thus may be candidates for assisted migration, see Fig 1b for results by type of animal, or Fig 2 for example candidate spp). Only 5% of spp. had a management plan mentioning "genetic rescue" (or the general concept), but 44% of candidate species had already used assisted migration (more frequent in fishes and mammals)). Note that italicized words are in a glossary at the end. Also note this paper does NOT include other connectivity strategies like habitat restoration, wildlife crossings, etc.

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.

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.

Cinner et al. 2012 is a study of 42 co-management arrangements for coral-dependent fisheries across 5 countries. Co-management led to more biomass than non-locally managed fished areas, and less than no-take closures (Fig 3). But see Fig 4 for key results (fish biomass was higher when markets were farther, and lower when more people replied on fishing for their primary income). They found just 54% of resource users saw co-management as improving their livelihoods (it seemed to benefit wealthier fishers w/ longer history of co-management and more agency).

Hughes et al. 2012 looks at how vulnerable different countries are to declining coral-dependent fisheries leading to reduced food security. Tables 2-4 have ratings of 27 countries vulnerability to declining fisheries impacting food security, as well as ratings of assets, flexibility, learning, and social organization. The most vulnerable countries are Indonesia, Liberia, Ivory Coast, and Kenya.

Cinner, J. E., McClanahan, T. R., MacNeil, M. A., Graham, N. A. J., Daw, T. M., Mukminin, A., Feary, D. A., Rabearisoa, A. L., Wamukota, A., Jiddawi, N., Campbell, S. J., Baird, A. H., Januchowski-Hartley, F. A., Hamed, S., Lahari, R., Morove, T., & Kuange, J. (2012). Comanagement of coral reef social-ecological systems. Proceedings of the National Academy of Sciences, 109(14), 5219–5222.

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.

Fitzpatrick, S. W., Mittan-Moreau, C., Miller, M., & Judson, J. M. (2023). Genetic rescue remains underused for aiding recovery of federally listed vertebrates in the United States. Journal of Heredity, March, 1–13.

Hughes, S., Yau, A., Max, L., Petrovic, N., Davenport, F., Marshall, M., McClanahan, T. R., Allison, E. H., & Cinner, J. E. (2012). A framework to assess national level vulnerability from the perspective of food security: The case of coral reef fisheries. Environmental Science & Policy, 23, 95–108.

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).

Schmitz, O. J., Sylvén, M., Atwood, T. B., Bakker, E. S., Berzaghi, F., Brodie, J. F., Cromsigt, J. P. G. M., Davies, A. B., Leroux, S. J., Schepers, F. J., Smith, F. A., Stark, S., Svenning, J.-C., Tilker, A., & Ylänne, H. (2023). Trophic rewilding can expand natural climate solutions. Nature Climate Change.


p.p.s. The photo is of a piece at the Renwick gallery in DC. The caption says: 'A mature oak tree produces about two thousand acorns a year, but only one in ten thousand acorns reaches maturity. Hudnall explains, “I think the idea of constant, repeated, tiny attempts for success, with the understanding that most will go nowhere, became a way for me to think about slow progress toward health in my own life.” '

Monday, April 3, 2023

April 2023 science summary



In case you missed it last month, check out the paper I co-authored on gender equity (I repeated the summary below, read or skim the whole paper if you have time, or at least read this blog overview).

The IPCC's latest synthesis report came out recently (and I have a short summary below), so the need to do more on climate change is on my mind.

Want to work on climate change via energy modernization at Pew? We're hiring for three jobs right now on a team that I'm super excited about. If you have any questions and/or may be interested please take a look at the posts and then let me know if you want to know more (and please pass them on):

  1. Senior Officer, Clean Grid and Energy

  2. Officer, State Campaigns

  3. Senior Associate, State Campaigns

Also - recently I am playing less w/ AI and reading more science myself, but thought this was a nice overview of strengths and weaknesses between ChatGPT, Bing, and Bard.

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


The IPCC's latest report (the AR6 synthesis) recently became available (here’s a direct link to the 36 page summary for policy makers). If you've been following all the IPCC reports, there is no new info here. But there is a persistent thread of clarity that I found helpful. Of the many findings, the ones that stood out to me are:

  1. The planet has warmed 1.1 degrees C already (1.6C on land)

  2. The world is currently roughly on track for 3.2 C of warming based on implemented policies (Fig SPM5a, w/ range from 2.2C to 3.5C).

  3. Good news - that means that "business as usual" is a little worse than RCP4.5 (Intermediate Emissions), ranging from Working Group III scenarios C5 to C7 (C7=High GHG emissions or SSP3-7.0). The high emissions (RCP8.5) scenario is pretty unlikely since it would require emissions to go up substantially over what is predicted. See Table 1 in Box SPM.1 for details.

  4. Bad news - look more closely at Fig SPM5a. The paths to limit warming to 2C or 1.5C assume sharp cuts starting in 2020, which means even if we act immediately, cuts would have to be much sharper to make those pathways feasible (the report notes the lack of both commitments and financing). We should still make the attempt, but remember there is no magic binary threshold, and every bit of warming we avoid has real value.

  5. They project climate impacts on species loss, human health, and food production (see Figure SPM3).

I was struck by two quotes in particular:

“Adaptation options that are feasible and effective today [JF reminder - elsewhere they note: "‘today’ refers to 2019"] will become constrained and less effective with increasing global warming.”

“All global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, and those that limit warming to 2°C (>67%), involve rapid and deep and, in most cases, immediate greenhouse gas emissions reductions in all sectors this decade.” (again, immediate relative to 2019).

The press release also notes that "Emissions should be decreasing by now [JF - again, that's 2019] and will need to be cut by almost half by 2030, if warming is to be limited to 1.5°C." This blog post highlights existing progress and what we need to do next.

AI side note: I asked Google Bard (their new beta AI) "What does the latest IPCC synthesis report say is the most likely amount of warming the world will experience?" and got a wrong answer: "The latest IPCC synthesis report says that the most likely amount of warming the world will experience is 1.5 degrees Celsius above pre-industrial levels.” (along with other text). But when I asked Bard "How much has the earth warmed so far, according to the latest IPCC synthesis report" it correctly states: "According to the latest IPCC synthesis report, the Earth has warmed by 1.1 degrees Celsius (2 degrees Fahrenheit) since the start of the industrial era."


Pearson et al. 2023 investigate whether restoring whale populations is likely to have a significant impact on climate mitigation. The idea being evaluated is that beyond carbon stored in whales themselves (which ends up in the deep sea when they die), that their poop stimulates a lot of phytoplankton growth which leads to net carbon capture (see Fig 1). The TL;DR results: whales and their poop MAY provide climate mitigation benefits but: we don't know yet, it'll take a long time to know, and additionality may be low (so don't sell whale carbon credits, please). See Box 1 for concerns w/ whale carbon credits, and box 2 for outstanding questions to be answered. They do note that whale recovery can be a "low regret" strategy, and I'd agree as long as it doesn't delay emissions reductions or otherwise pull resources from more proven climate solutions.


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.


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.


Moore et al. 2023 is an interesting metanalysis of how vehicle collisions impact different wildlife populations around the world. Their 83 studies (of 150 populations of 69 species) are not representative / proportional of all wildlife. Most are of either even-toed ungulates (like elk and pigs) or carnivorans (like bear and big cats), roadkill studies inevitably concentrate on places where road mortality is significant, and a lot of the studies have really small samples. But they make a good case that it's a more important issue than is typically understood. Of the 58 studies that looked at roadkill as a % of all mortality over half found roadkill to be <15%, but 25 studies found 15-45% mortality from roadkill, 6 were 45-60%, and 3 were 60-80% (although they don't provide the data in a table, so I wonder if those 3 studies are weak / small N / outliers). They also found roadkill was the biggest source of mortality for 28% of populations studies, and it was in the top 3 for virtually all studies (again, likely a mix of it being an important threat AND a skewed study selection). Check out Figure 4A and 4B to see the biological orders hit hardest by roadkill (Tasmanian devils lost the most per year, opossums had the highest share of mortality from roads).

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: or a short blog at


IPCC (2023). AR6 Synthesis Report. (accessed Mar 24, 2023).

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. or

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.

Moore, L. J. ., Petrovan, S. O., Bates, A. J., Hicks, H. L., Baker, P. J., Perkins, S. E., & Yarnell, R. W. (2023). Demographic effects of road mortality on mammalian populations: a systematic review. Biological Reviews, 3.

NatureServe. (2023). Biodiversity in Focus: United States Edition.

Pearson, H. C., Savoca, M. S., Costa, D. P., Lomas, M. W., Molina, R., Pershing, A. J., Smith, C. R., Villaseñor-Derbez, J. C., Wing, S. R., & Roman, J. (2023). Whales in the carbon cycle: can recovery remove carbon dioxide? Trends in Ecology & Evolution, 38(3), 238–249.



p.s. The photo is of a dead copperhead I found on a road near Luray, VA