Wednesday, March 17, 2021

Learning from failure


Photo ©Jeff Reed 2.0 Generic (CC BY-NC-SA 2.0)

Do you find it difficult to even talk about failure, let alone learn from it? I've got a couple of new blogs which may be helpful.

The first one summarizes barriers to learning from failure:

The second one has suggestions to make learning from failure easier and more productive:

Monday, March 1, 2021

March 2021 science summary

Ice balls on dead flowers


As I write this, everything is encased in ice, so reading science with a cup of tea is pretty appealing!

I've summarized a few very useful articles on protected areas, all of which have useful insights (where to cite PAs for different goals, how they perform under climate change, and how to measure how well they protect a range of habitat types).

I've also got a paper on how flood damages have changed and how that relates to changing precipitation (and what we can expect with climate change), and one on shipping fuel regulations in China (impact on air quality, cost, and benefit:cost ratio).

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


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 extent, 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.

Jantke et al. 2019 proposes a clever way to ensure that "% protected" goals like 30 by 30 (protecting 30% of a country on land and water by 2030) don't focus on easy to protect habitat types while other habitat types remain mostly unprotected. They suggest reporting “mean target achievement” where the % protected of each habitat type would be averaged and compared to a habitat-level goal (See section 2.2 for the equation - crucially achievement maxes out at 100% so overprotection in one habitat can't compensate for underprotection in another). They use Australia's Commonwealth Marine Reserve as an example; it protects 43% of the five marine regions it covers, but still falls short of its goal of protecting at least 10% of each of the 53 bioregions within it. This is a great complement to the total % protected indicator, as ecological representation has badly lagged behind total protection, and the rush to protect a lot more area very quickly will make it very tempting to focus on the easiest habitats to protect even though many other habitats have little to no protection.

Simmons et al. 2021 (a non-peer-reviewed white paper) looks at a few options to meet 30 by 30 in the U.S. with four different focal objectives (all also minimizing acquisition cost): area alone, carbon sequestration and avoided emissions, landscape connectivity, and climate-resilient species and habitat. It’s a fairly coarse and simplistic assessment, but it does a good job highlighting the kinds of tradeoffs to consider when deciding which lands we advocate for protecting. Check out Figure 2  which shows how their four scenarios perform (on cost, ecosystem representation, and climate mitigation) and where they would protect across the lower 48 states. They close with recommending clear objectives to prioritize where to protect, focus protections on threatened areas, develop metrics to track progress and impact (including on issues like social equity), and use diverse options (beyond traditional protected areas) to provide protection. Check out the appendix for maps showing which areas are already somewhat protected (as GAP 3).

Zhu et al. 2021 analyzes forested protected areas (PAs) in the Appalachians and asks how well they will provide future habitat to birds, mammals, reptiles, and amphibians after climate change (allowing for migration). They found that climate change would worsen suitable habitat that PAs provide for mammals and amphibians, while improving habitat suitability for birds and reptiles (if they are freely able to migrate, if not all groups of species would fare worse). They also found that threatened species are more likely to have their habitat worsen (see Table 2); NatureServe's global ranks G1->G4 would see a decline in suitable habitat (although only G3 was statistically significant, and G5 significantly improved) while endangered species did significantly worse (with vulnerable and other less threatened species seeing smaller and non-significant changes). They recommend focusing protection on areas of high species richness in the Blue Ridge (and the Cumberland plateau) to a lesser extent) which will remain suitable habitat under climate change. One key caveat: the main paper assumed a high emissions scenario (RCP 8.5), with a more moderate climate scenario (RCP 4.5) modeled in Appendix S4 / Table S2.


Davenport et al. 2021 analyzed historic data on precipitation and flood damages in the US. They found that as extreme precipitation (with maximum monthly precip being the most important) has increased over the past 30 years, so have flood damages. By comparing the recent past (30 yrs) to the prior 130 years, they estimate about 1/3 of recent flood damages ($73 billion) are attributable to the change in precipitation (Fig 3). They don't estimate how much of that is specifically due to anthropogenic climate change. Fig 5 has estimates of what we can expect in the future as climate change continues: the two left columns in the bottom row are the most useful. They represent the optimistic (column A) and pessimistic (column B) change in the top 1% of monthly precip. Note that even in regions expected to get dryer, the MAXIMUM rainfall will also increase (think flashier and more variable rainfall).


Zhu & Wang 2021 looks at the impact of regulations on shipping fuel in China. They found that ports w/ no penalty for non-compliance did not see improvements in air pollution, but others did. The total cost of the regulations was 4 times the price difference of the fuels, but the health benefits from the reduced pollution were >30 times as high as the cost.



Davenport, F. V., Burke, M., & Diffenbaugh, N. S. (2021). Contribution of historical precipitation change to US flood damages. Proceedings of the National Academy of Sciences, 118(4), e2017524118.

Jantke, K., Kuempel, C. D., McGowan, J., Chauvenet, A. L. M., & Possingham, H. P. (2019). “Metrics for evaluating representation target achievement in protected area networks.” Diversity and Distributions, 25(2), 170–175.

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.

Simmons, B.A., Nolte, C., McGowan, J. (2021). Delivering on Biden’s 2030 Conservation Commitment. GDPC Working Paper 001/2021. Global Development Policy Center, Boston University.

Zhu, J., & Wang, J. (2021). “The effects of fuel content regulation at ports on regional pollution and shipping industry.” Journal of Environmental Economics and Management, 106, 102424.

Zhu, G., PapeĊŸ, M., Giam, X., Cho, S., & Armsworth, P. R. (2021). “Are protected areas well-sited to support species in the future in a major climate refuge and corridor in the United States?” Biological Conservation, 255(March), 108982.