Friday, July 1, 2022

July 2022 science summary

Bromeliad fly (Copestylum) on spiderwort (Tradescantia)


This month is another grab bag: one paper on equity in fire management, two on biodiversity data, one asking how much conservation has helped species, and one pretty bad one on how ag practices impact nutrients.

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

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.:

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.

Before threatened species can get protection, they need to be assessed to document how vulnerable they are. But there is a substantial backlog of species waiting to be assessed. Levin et al. 2022 offers a fairly simple (but ultimately unsuccessful) way to re-prioritize unassessed species for the IUCN red list to allow a better chance of assessing the ones that are in trouble so they can get protection. They use a rapid estimate of "extent of occurrence" (the species' range and spatial distribution of threats) as a proxy for vulnerability. At first it's exciting to see that it was 92% accurate at identifying which species were of the Least Concern (showing potential to flag species not worth assessing). But two questions are more relevant (and Fig 1 has the answers): what % of vulnerable species does it correctly recommend assessing (40%) and what % of recommendations for assessment are for species that are actually vulnerable (23%). The discussion has interesting notes on some of the aspects that confused the model (like 5 ash app threatened by Emerald Ash Borer and the American Chestnut threatened by blight) - widespread spp. hit hard by invasives are challenging to accurately assess using simple approaches like this. Hopefully the next iteration of the tool will be more successful, if they could substantially reduce false negatives for vulnerable species it could provide assessment priorities directly, or if they could substantially reduce false positives for vulnerable species it could help by indicating species that likely shouldn't be assessed.

Jellesmark et al. 2022 is a global (see Fig 1 map) preprint looking at how conservation has impacted targeted vertebrate species (by comparing pairs of populations targeted for conservation with those in the same country that did not receive conservation attention). I honestly don't know enough about the underlying data source (Living Planet Database) to speak to the reliability of their results (I'll wait for peer review for that, there is at least one very important typo where they use "invertebrate" when they clearly mean "vertebrate"). They found that population size of assessed vertebrates dropped 24% over 46 years, but estimate that without conservation it would have dropped 32% (and this likely underestimates the impact of conservation). They split out conservation actions into 7 groups (land/water protection, land/water mgmt, species mgmt, education/awareness, law/policy, livelihoods/incentives, and external capacity building), and capacity building followed by the first three showed the strongest results (Fig 5).

Montgomery et al. 2022 asks how nutrients from ‘regenerative’ farms (that use no-till, crop  rotations, and cover crops) differ from other farms, but I wouldn't recommend it. This paper is pretty weak methodologically, results were inappropriately highlighted and over-interpreted, and the results I initially planned to write about didn’t hold up when I looked at raw data. Some key caveats: it is a very small sample size, 4/5 authors have financial interests the paper furthers, only one author appears to be a scientist (a geomorphologist), and the methods are thin and read like they may have gone looking for pairs of farms that would support the desired narrative (plus they used a very rough method to measure organic matter). At first I thought the most interesting / meaningful results are for cabbage: 10 assessed nutrients were substantially higher on regenerative farms, compared to 4 that were the same, 4 that were substantially lower, and 3 not assessed. But when you dive in, that 70% difference in vitamin E is from 0.004 to 0.007 mg/100g (essentially nil). Ditto with wheat results, 50% more calcium than “almost none” is still almost none. The animal results are hard to interpret because they don’t provide enough detail on differences between ‘regenerative’ vs. ‘conventional’ (although findings that grass-finished beef have more nutrient content have been reported in other lit, in alignment w/ results here). Some results look more meaningful (20% more vitamin C in cabbage is worthwhile) but there is such variation in the soil organic matter and soil health across the farms it’s really hard to know what is significant and what is accidental. One last note - 'regenerative' here almost certainly means 'genetically modified’ for most crops, since it’s hard to do no-till without them.


Anderson, S., Plantinga, A., & Wibbenmeyer, M. (2020). Inequality in Agency Responsiveness: Evidence from Salient Wildfire Events (Issue December).

Jellesmark, S., Blackburn, T. M., Dove, S., Geldmann, J., Visconti, P., Gregory, R. D., McRae, L., & Hoffmann, M. (2022). Assessing the global impact of targeted conservation actions on species abundance. BioRxiv, 2022.01.14.476374.

Levin, M. O., Meek, J. B., Boom, B., Kross, S. M., & Eskew, E. A. (2022). Using publicly available data to conduct rapid assessments of extinction risk. Conservation Science and Practice, November 2020, 1–9.

Montgomery, D. R., Biklé, A., Archuleta, R., Brown, P., & Jordan, J. (2022). Soil health and nutrient density: preliminary comparison of regenerative and conventional farming. PeerJ, 10, e12848.

Saran, S., Chaudhary, S. K., Singh, P., Tiwari, A., & Kumar, V. (2022). A comprehensive review on biodiversity information portals. Biodiversity and Conservation, 0123456789.

p.s. This photo is of what I think is a bromeliad fly (Copestylum) on a Tradescantia flower in my garden. First time I have seen one!

Wednesday, June 1, 2022

June 2022 science summary

Red-winged blackbird


This month I only have three science articles but they're all good'uns.

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

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.

Nicholson et al. 2021 is chock full of useful diagrams and lists. 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.

There are good remote sensing data for land cover change, worse but decent data for land use change, but generally not much on degradation (which means we can underestimate ecological decline). Swaty et al. 2021 describe a "Vegetation Departure" (VDEP) spatial data set for the US which gets at this. This includes whether early or late successional stages are over-represented or under-represented (think of a logged forest w/ no old growth left but plenty of young forest, or a grassland being taken over by denser shrubs which were historically less common). They highlight several limitations of the existing LANDFIRE VDEP data (which focuses on canopy cover and height), and recommend that users consider other attributes that are important to their ecosystems of interest (e.g., biodiversity, wildlife populations, wildfire risk, etc.).


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.

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.

Swaty, R., Blankenship, K., Hall, K. R., Smith, J., Dettenmaier, M., & Hagen, S. (2021). Assessing Ecosystem Condition: Use and Customization of the Vegetation Departure Metric. Land, 11(1), 28.

p.s. The photo above is of a red-winged blackbird bathing in the Potomac River at Dyke Marsh

Monday, May 2, 2022

May 2022 science summary

Lizard on a porch screen


This month I have a few science articles on freshwater, two on climate change and forest management, and one big one on biodiversity.

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

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 and especially the interactive maps of their data.

Littlefield and D'Amato 2022 looks at trade-offs between maximizing forest carbon and maximizing biodiversity and habitat quality. In particular, they note that many species require disturbance (like fire or tree removal), while maximizing carbon generally involves promoting uniformly dense and mature trees. They note that robust data looking at how different species respond to forest management are surprisingly scarce, but offer several case studies where as tree biomass increased, wildlife abundance and/or diversity has declined. They recommend that conservation planning consider climate adaptation, which means keeping landscape diversity, complexity, and connectivity (accepting that means some reduction in potential carbon), and that we explicitly discuss and recognize trade-offs where they exist.

Stephenson et al. 2014 is a global analysis of how carbon sequestration by 403 tree species change as they grow and age. 87% of tree species sequester more annual carbon per year as they get bigger (even when they get huge). On average a 1m diameter tree sequesters about triple the carbon as a 1/2m diameter tree (similar to the trunk cross-section ration of 4:1). The biggest trees can add ~0.55-0.72 t biomass (not C, which would be much lower) per year (Fig 3). However, they note that at the forest level, as an even-aged stand gets older the annual carbon sequestered per land area goes down (as trees die, total sequestration declines despite remaining big trees sequestering more. Ideally forest management should think about 1) impacts on carbon pools (how much harvested tree biomass will be lost to the atmosphere), 2) impacts on carbon sequestration, and 3) impacts on forest ecology (both mature / older trees, and disturbances and younger trees have important roles).

Broadley et al. 2022 is a global assessment (although w/ ~1/4 of studies coming from the US) of how marine fishery productivity (including invertebrates) depends on rivers. Their headline finding is that 72% of 276 fished species (77% of global catch by mass) are linked to river flows at some point in their life cycle, and 83% eat food linked to river flows. The biggest link is occasionally going to estuaries to eat (77% of species) as opposed to diadromous or estuarine-dependent species (23% of species), see Fig 5 for a map of where they're distributed. They also offer a conceptual review of how rivers influence fisheries by focusing on science literature for the top 10 fishery species by catch mass. They conclude that rivers influence fisheries via physical changes (flow quantity, timing, and quality [sediment, nutrients, salinity, temperature, etc.]), biological response of marine species to those physical changes (e.g. nutrients from a river increasing algae which zooplankton and fish respond to, changes in spawning in response to freshwater mixing, migration, etc.), and changes in fisher behavior and fishery productivity resulting from those biological changes (see Table 1). They recommend an integrated planning approach to rivers (including dam management) and marine fisheries.

Pennock et al. 2022 makes a case that rivers with relatively natural flow regimes should be priorities for conservation (specifically protection that limits consumptive water use or otherwise alters flow). They look at four tributaties of the Green River (which feeds the Colorado River): the White, Price, San Rafael, and Duchesne Rivers. Only the White River has a relatively natural flow regime (although median spring discharge is still down 25% relative to before 1949, and summer baseflow by 29%), and spring flow in the Duchesne and San Rafel are down ~80%. That drop in flow accompanies habitat degraded in several ways: less large woody debris, narrower channels, less regeneration of cottonwoods, loss of native fish spp, etc. They also point out that even dams managed for environmental flow has fallen well short of natural flood regimes.

Maasri et al. 2022 is a new global freshwater research agenda. They have 15 recommendations in 5 themes: 1) Data infrastructure (compile and integrate data sources on freshwater biodiversity, mobilize and share existing data w/ stakeholders, and develop accessible databases), 2) Monitoring (coordinate existing FW biodiversity monitoring and move towards global consistency, expand monitoring to places and species currently overlooked [like fungi and protists], and develop new monitoring methods [like eDNA, remote sensing, citizen science, etc.]), 3) Ecology (better understand how biodiversity relates to ecosystem health and services, study how biodiversity responds to multiple stressors, and study species and ecosystem responses to global change), 4) Management (rigorous assess how well restoration works, develop management strategies aligned with "Nature Futures" scenarios based on positive human-nature relationships, and develop watershed-based integrated management and restoration programs including dam building and operation), and 5 Social ecology (co-produce solutions to conflicts between conservation and people who use freshwater systems, develop adaptive management strategies that address trade-offs with a broad coalition of participants, and promote citizen science and participatory research). I was surprised that they left off legal research into how policy mechanisms for water management are working (or not), and am somewhat skeptical that agendas like this get used, but it's a nice overview of some needs and gaps.


Broadley, A., Stewart-Koster, B., Burford, M. A., & Brown, C. J. (2022). A global review of the critical link between river flows and productivity in marine fisheries. Reviews in Fish Biology and Fisheries, 0123456789.

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.

Littlefield, C. E., & D’Amato, A. W. (2022). Identifying trade‐offs and opportunities for forest carbon and wildlife using a climate change adaptation lens. Conservation Science and Practice, 4(4), 1–14.

Maasri, A., Jähnig, S. C., Adamescu, M. C., Adrian, R., Baigun, C., Baird, D. J., Batista‐Morales, A., Bonada, N., Brown, L. E., Cai, Q., Campos‐Silva, J. V., Clausnitzer, V., Contreras‐MacBeath, T., Cooke, S. J., Datry, T., Delacámara, G., De Meester, L., Dijkstra, K. B., Do, V. T., … Worischka, S. (2022). A global agenda for advancing freshwater biodiversity research. Ecology Letters, 25(2), 255–263.

Pennock, C. A., Budy, P., Macfarlane, W. W., Breen, M. J., Jimenez, J., & Schmidt, J. C. (2022). Native Fish Need A Natural Flow Regime. Fisheries, 47(3), 118–123.

Stephenson, N. L., Das, A. J., Condit, R., Russo, S. E., Baker, P. J., Beckman, N. G., Coomes, D. A., Lines, E. R., Morris, W. K., Rüger, N., Álvarez, E., Blundo, C., Bunyavejchewin, S., Chuyong, G., Davies, S. J., Duque, Á., Ewango, C. N., Flores, O., Franklin, J. F., … Zavala, M. A. (2014). Rate of tree carbon accumulation increases continuously with tree size. Nature, 507(7490), 90–93.


Tuesday, March 1, 2022

March 2022 science summary

Winter biking


I've got a mix of papers this month but most relate to climate change (priorities for mitigation and adaptation, impacts on flooding, and how to plan for it) plus a couple of wildlife movement. 

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

Dreiss & Malcom 2022 is an analysis of 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 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.

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 hotpsots is likely to miss critical refugia and corridors to help ensure resilience to climate change.

Wing et al. 2022 modeled increasing US flooding risks due to both climate change (by 2050 under RCP4.5, which is 'medium' emissions but still means aggressive decarbonization) and changing populations. Note that the paper uses 'risk' in the engineering sense: likelihood of impact times magnitude of impact (so risk is reported as expected annual $ losses due to floods). Those losses are expected to go up 26% just from climate change (calculated at the building level based on current population data), but considering both climate change and population change they predict almost twice as many people will be impacted by flood each year (with that impact driven largely by population growth). The highest current flood risk is in predominantly white and extremely poor counties (partly b/c very poor people in areas at risk of floods have few financial assets not vulnerable to floods, so their relative risk is higher). The counties with the highest % Black population are expected to see twice as much risk increase by 2050 as counties with the fewest Black people. This is due a mix of increasing flooding risk in the Deep South, and the relatively low current risk of mostly Black counties. You can read more about this at

Brown et al. 2022 has a good overview of recent improvements to incorporating climate change into conservation planning via the Conservation Standards (aka Open Standards for the Practice of Conservation). If you're not familiar with the Standards, this paper will be a bit overwhelming, but still has useful tidbits. Jump to figure 4 for a very helpful diagram of physical changes expected to result from climate change, and which of these changes make sense to classify as "direct climate threats" (in red text). What I love about this is it helps you move past (climate change will affect everything) and identify the specific changes that a) will affect focal species and ecosystems, and b) which you can affect via conservation. So rather than focusing on changes to rain, they identify decreased water availability and increased risk of landslides as climate threats. Then Fig 5b shows how the climate threats are integrated w/ other direct threats and linked to conservation targets (the species and ecosystems being prioritized for action). If you can handle switching examples, Figs 6 and 7 show how to move from a situation model (linking threats to targets and identifying possible strategies) to a results chain (showing the desired interim results and ultimate impacts of a strategy). There is some updated guidance available since this was published on the CMP web site.

Merkle et al. 2022 addresses the problem that species which favor returning to fixed places to forage / breed / shelter have a hard time adjusting to habitat loss and resulting fragmentation. Figure 2 has a good example: mule deer in WY staying true to winter range despite oil & gas development, which the authors give as an example of an 'ecological trap' due to 'site fidelity' (they keep coming back even if they have better alternatives). They call for more research on what drives site fidelity (genetics, environmental conditions, or a mix), and for conservation plans to account for site fidelity rather than assuming animals will choose the best habitat possible.

Vynne et al. 2022 is a global analysis to find terrestrial ecoregions where only 1-3 large mammals (>33 lb, 298 species) are missing from the mammals that present 500 years ago (Fig 2 has a map of those results). Given the impact large mammals have on ecosystems, the idea is that getting back to the full suite of mammals that used to be there will have broader effects. But this is an assumption the authors make, rather than a conclusion of the analysis (most news headlines have implied the latter). The best known example of that is the impact of reintroducing wolves to Yellowstone leading to a trophic cascade (although unfortunately those effects have been widely exaggerated due to non-random aspen sampling and failing to account for confounding effects of human hunting and changes in streamflow due to climate). Their 30 priority ecoregions for reintroduction / restoration are in Table 2 and Figure S3. They note the challenges in reintroducing predators in particular, including the need to plan to avoid human conflict and difficulty of securing protection over large areas to allow for connectivity).


Brown, M. B., Morrison, J. C., Schulz, T. T., Cross, M. S., Püschel-Hoeneisen, N., Suresh, V., & Eguren, A. (2022). Using the Conservation Standards Framework to Address the Effects of Climate Change on Biodiversity and Ecosystem Services. Climate, 10(2), 13.

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.

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.

Merkle, J. A., Abrahms, B., Armstrong, J. B., Sawyer, H., Costa, D. P., & Chalfoun, A. D. (2022). Site fidelity as a maladaptive behavior in the Anthropocene. Frontiers in Ecology and the Environment, 1–8.

Vynne, C., Gosling, J., Maney, C., Dinerstein, E., Lee, A. T. L., Burgess, N. D., Fernández, N., Fernando, S., Jhala, H., Jhala, Y., Noss, R. F., Proctor, M. F., Schipper, J., González‐Maya, J. F., Joshi, A. R., Olson, D., Ripple, W. J., & Svenning, J. (2022). An ecoregion‐based approach to restoring the world’s intact large mammal assemblages. Ecography, 1–12.

Wing, O. E. J., Lehman, W., Bates, P. D., Sampson, C. C., Quinn, N., Smith, A. M., Neal, J. C., Porter, J. R., & Kousky, C. (2022). Inequitable patterns of US flood risk in the Anthropocene. Nature Climate Change.

p.s. If you'd like to keep track of what I write as well as what I read, I always link to both my informal blog posts and my formal publications (plus these summaries) at
p.p.s. As shown in the pic above - I am a committed winter biker, and my wife and I very much enjoyed Arlington's winter bike games recently!

Tuesday, February 1, 2022

February 2022 science summary

Pineapple the 29" tall mini horse

Hi all,

January was a bit bananas so I've only got summaries of three papers on protected areas this month (efficacy of Indigenous protected areas, recommendations to improve North American connectivity, and the importance of inventoried roadless areas in US national forests).

If you know someone who wants to sign up to receive these summaries, they can do so at

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.

Barnett et al. 2021 model ecological connectivity across North America to make recommendations for protected areas that best retain connectivity. The interesting part of the paper is the comparison between circuit theory and least cost approaches and how they affect recommendations. Least cost assumes species have perfect knowledge about the landscape, which is obviously untrue but over generations if individuals explore a bit on their route those routes can improve as they learn. Having the map of priorities is not terribly useful, especially since this one is based on human modification data but w/ no calibration or validation using wildlife data. The paper I wish they had written was to actually compare both modeling approaches with empirical data on wildlife movement! Essentially asking what each model gets right and wrong, and make recommendations about which approach is more useful / accurate in what context, and whether a new paradigm is needed. In my own work I’ve learned to deeply discount the value of any model which isn’t first calibrated against real world data, and then validated against other real world data not used to build the model.

Dietz et al. 2021 look at inventoried roadless areas (IRAs) in national forests in the US lower 48 states, and how important they are to vertebrate wildlife species of conservation concern (SCC - defined broadly as any of: listed under Endangered Species Act, IUCN vulnerable or worse, or NatureServe vulnerable or worse either nationally or globally, 31% of all vertebrate wildlife species). They found 57% of SCC had at least some habitat on roadless areas, and 99% of the area in IRAs provided habitat for at least one SCC. Since they're looking at about 1/3 of wildlife species, it's not shocking that intact / undeveloped forests typically provide habitat to at least SOME of those species (although as they note, since IRAs don't exist for non-forest habitats it's still impressive). The policy implications are tricky - the authors argue IRAs are good candidates for strengthening protection, but on the other hand one could argue that focusing on intact areas with less protection than IRAs would offer more benefit.

Barnett, K., & Belote, R. T. (2021). Modeling an aspirational connected network of protected areas across North America. Ecological Applications, 31(6), 1–7.

Dietz, M. S., Barnett, K., Belote, R. T., & Aplet, G. H. (2021). The importance of U.S. national forest roadless areas for vulnerable wildlife species. Global Ecology and Conservation, 32(November), e01943.

Sze, J. S., Carrasco, L. R., Childs, D., & Edwards, D. P. (2021). Reduced deforestation and degradation in Indigenous Lands pan-tropically. Nature Sustainability, 2.


p.s. Pictured above is Pineapple the 29" tall mini horse. I took this photo at an event where kids in hospice (or with family members in hospice) got to hang out with horses

Wednesday, January 5, 2022

Best of 2021 science summaries

Jazzy snowman


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 (, and my colleague Peter Edwards hosted the next one (focused on Latin America, the Caribbean, and African contexts, I've added links to the videos on this blog post where I've been collecting some related resources on the topic:

If you know someone who wants to sign up to receive these summaries, they can do so at 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:

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! 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:
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 ( 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):

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:

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.