Wednesday, September 1, 2021

September 2021 science summary

Climate emission curves

Greetings,

This month is all about climate change (the photo above is from mini golf course in Brooklyn, where the three paths represent emissions scenarios).

First - I want to clarify something from last month's update. I mentioned that big old trees are especially important for carbon sequestration, and that increasing the length of time between forests being logged and/or leaving the biggest trees can be helpful to retain that carbon. But the term "proforestation" that I used is apparently commonly used to mean no forest management at all. That means eliminating any tree cutting at all (not just commercially, but even for pest management, fire control, or ecological goals). While logging can have environmental downsides (including for carbon), wood products are also relatively sustainable, and cutting trees is one of several important forest management tools that may be useful even in lands managed primarily for conservation. In cases where not cutting trees increases the risk of severe fire, that could even lead to worse outcomes for carbon sequestration and storage. Apologies for the poor choice of language.

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CLIMATE CHANGE:
You probably have heard that the 2021 IPCC report came out this month: https://www.ipcc.ch/report/ar6/wg1/ Don't feel like reading 1800 pages or even the 90 page summary or 215 page FAQ? Check out the 2 page 'headline statements' here:  https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Headline_Statements.pdf
The one thing to highlight for me is that limiting warming to 1.5C is now harder but not impossible (requiring net zero by 2055 w/ 90% gross emissions reductions). Current policies agreed to under Paris would still lead to 3C warming by 2100. One finding that I read about in this New York Times article (https://www.nytimes.com/2021/08/09/climate/climate-change-report-ipcc-un.html) really struck me: a bad heat wave that used to happen every ~50 years is now happening every ~10 years, and will happen every ~5 years at 1.5C or nearly annually at 4C. Don't miss this interactive tool to explore the results (and note you can download spatial data via the "share" icon): https://interactive-atlas.ipcc.ch/

Want some good news about climate? Costa et al. 2021 have a brief overview of the use of GWP* as a way to calculate the global warming potential of methane (CH4) more accurately than GWP100 (100 year warming). This is super-tricky and took me a while to wrap my head around, but the basic issue is that because methane is naturally breaking down over time, GWP* looks at emissions 20 years ago (which are now breaking down into CO2) to understand net changes in CH4 (as opposed to GWP100 which treats it as constant over 100 years). It means that relatively small reductions in biogenic methane (mostly from livestock and soil) emissions could get us to a stable point where globally methane is emitted and broken down at the same rate. Since the CO2 that feeds into biogenic CH4 is pulled out of the atmosphere via feed, that means it's arguably easier than we thought earlier to get to the point where globally biogenic methane isn't causing warming. Two big caveats: 1) this doesn't apply to fossil methane (where the end product of CO2 is pulled out of the ground, leading to a net increase), 2) this only makes sense when estimating global methane levels, and NOT in thinking about reductions at a local level. The latter point is important - a company or country could use this metric to make small reductions in livestock emissions and "take credit" for the breakdown of high past levels, and argue they are carbon negative (they are not). But if you take away the attribution issue, and focus on estimating warming, this offers an improvement. Let me know if this is still confusing to you, and/or you think I got this wrong!

Green et al. 2019 quantify the well known issue of climate and soil moisture having a big impact on carbon sequestration. Using climate projections (now out of date w/ the 2021 IPCC report) they find that as climate gets more variable, carbon sequestration and storage by plants will strongly decline (offsetting CO2 fertilization by 2060 under conservative assumptions). By 2085 carbon sequestration will have fallen to half of what it would have been without the moisture variability. The potential  carbon lost through drought and fire exceeds potential carbon gains from unusually wet conditions. This is mostly b/c plants get a lot less productive under drought, while too much water doesn't spur lots of growth (and can even be harmful with floods). Surprisingly they focused on plant biomass rather than modeling soil carbon changes, nor did they look at the impact of this changing soil moisture on methane or nitrous oxide soil emissions. There's a summary of this paper at https://www.carbonbrief.org/climate-changes-impact-on-soil-moisture-could-push-land-past-tipping-point

Fox et al. 2018 looked at how common parasites in lambs impact methane production. I was intrigued by the title (which says they drive a 33% increase in 'methane yield') which seemed to indicate a huge potential to reduce GHGs from lamb through medical treatment. But that is a fairly artificial metric of methane emissions per mass of feed. A more meaningful metric is total methane emissions (fig 2), which were highest in healthy lambs eating a normal diet, moderately lower in parasitized lambs, and slightly lower than that in healthy lambs eating less to control for the weight loss impact of parasites. Usually the main metric is emissions per kg of meat; I estimated this from final body weight using table 1 and figure 2 and it looks like healthy lambs emitted ~1.83 daily g CH4 / kg final body weight, parasitized lambs emitted ~1.67 daily g CH4 / kg final body weight, and healthy lambs on a restricted diet emitted ~1.62 daily g CH4 / kg final body weight. My take away from this paper is that eliminating parasites is unlikely to deliver much climate mitigation (in this case without dietary adjustment would INCREASE GHGs), although it may be desirable from an animal welfare or efficiency perspective.

REFERENCES:

Costa Jr, C., Wironen, M., Racette, K., & Wollenberg, E. (2021). Global Warming Potential* (GWP*): Understanding the implications for mitigating methane emissions in agriculture. CCAFS Info Note. Wageningen, The Netherlands https://cgspace.cgiar.org/handle/10568/114632

Fox, N. J., Smith, L. A., Houdijk, J. G. M., Athanasiadou, S., & Hutchings, M. R. (2018). Ubiquitous parasites drive a 33% increase in methane yield from livestock. International Journal for Parasitology, 48(13), 1017–1021. https://doi.org/10.1016/j.ijpara.2018.06.001

Green, J. K., Seneviratne, S. I., Berg, A. M., Findell, K. L., Hagemann, S., Lawrence, D. M., & Gentine, P. (2019). Large influence of soil moisture on long-term terrestrial carbon uptake. Nature, 565(7740), 476–479. https://doi.org/10.1038/s41586-018-0848-x

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

Sincerely,
 
Jon
 
p.s. Here's one more picture from the climate change mini golf course, showing a polar bear on melting ice floes 

Monday, August 2, 2021

August 2021 science summary

Hi,

This month is a grab bag of a few articles on different topics I've been meaning to read. Sorry for the lack of a theme!

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BIODIVERSITY / ECOLOGY:
Maron et al. 2021 offers seven guidelines to set robust biodiversity goals (aimed at the Global Biodiversity Framework [GBF] under CBD), summarized in a nice diagram in Fig 1. 1. recognize limits to "net outcome" approaches (determine which spp and ecosystems are irreplaceable), 2. use net outcomes where needed since some losses are unavoidable, 3. specify a timeline for net outcome goals (a reference year and a target year), 4. set goals for net gains (since a reference year like 2020 has some spp. and ecosystems which have experienced high historic loss, so net gaines are needed to persist), 5. capture key biodiversity (with distinct goals for ecosystems, spp., and genetic diversity), 6. avoid unintended substitutions by ensuring any losses to one species (or ecosystem) is balanced with gains to a different one only if the losses are to a relatively unthreatened component, and 7. set ambitious goals (achievable, but more than adequate). They note several changed needed to the post-2020 GBF to meet these criteria.

Lutz et al. 2018 asks how important the biggest trees in forests are across the world. My favorite figure is that the biggest 1% in diameter made up ~50% of the aboveground biomass (of trees bigger than 1 cm), although with lots of variation by forest. If you use a consistent threshold of trees >2' in diameter instead of the top 1%, they're ~40% of biomass on average. Forests where the biggest trees took up a bigger % of total biomass tended to have fewer species in that top size class. They point out that for carbon sequestration, these big trees are super important, which Bill Moomaw has also emphasized in advocating for 'proforestation' where we just leave forests alone for longer before logging them as the rate of sequestration goes up as they get really big.

Hall et al. 2021 is about Circuitscape (software to analyze wildlife connectivity at the landscape scale) and the advantages of having ported it over to Julie (a high-performance computing language). From figure 3 it looks like the new version is about 7 times as fast as the python version, and it runs as a standalone without needing to know Julia. They make the broader point that collaborating with computer scientists can reduce costs and improve efficiency, allowing more conservation to get done.


SOCIAL SCIENCE:
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.


REFERENCES:

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

Hall, K. R., Anantharaman, R., Landau, V. A., Clark, M., Dickson, B. G., Jones, A., Platt, J., Edelman, A., & Shah, V. B. (2021). Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment. Land, 10(3), 301. https://doi.org/10.3390/land10030301

Lutz, J. A., Furniss, T. J., Johnson, D. J., Davies, S. J., Allen, D., Alonso, A., Anderson-Teixeira, K. J., Andrade, A., Baltzer, J., Becker, K. M. L., Blomdahl, E. M., Bourg, N. A., Bunyavejchewin, S., Burslem, D. F. R. P., Cansler, C. A., Cao, K., Cao, M., Cárdenas, D., Chang, L.-W., … Zimmerman, J. K. (2018). Global importance of large-diameter trees. Global Ecology and Biogeography, 27(7), 849–864. https://doi.org/10.1111/geb.12747

Maron, M., Juffe-Bignoli, D., Krueger, L., Kiesecker, J., Kümpel, N. F., ten Kate, K., Milner-Gulland, E. J., Arlidge, W. N. S., Booth, H., Bull, J. W., Starkey, M., Ekstrom, J. M., Strassburg, B., Verburg, P. H., & Watson, J. E. M. (2021). Setting robust biodiversity goals. Conservation Letters, May, 1–8. https://doi.org/10.1111/conl.12816

Sincerely,
 
Jon

Thursday, July 1, 2021

July 2021 science summary

Milkweed beetle

 Hello,


This month I've got a few papers on protected areas and three important papers about the role of forests in climate change. The photo above is just a milkweed beetle from my garden whose eye is bisected by its antenna!

Since there's been a lot of interest lately in protected areas and 30x30, I pulled together summaries of some of my favorites here: http://sciencejon.blogspot.com/2021/06/some-papers-on-30-x-30-and-protected.html

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon



PROTECTED AREAS:
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.

Devillers et al. 2015 argues that marine protected areas (MPAs) have largely been cited in remote areas with low threats that the MPAs are intended to address. They point out that politics drive MPAs to be established in places that minimize costs and conflicts with commercial interests, but that MPAs that avoid potential conflicts will by definition have low impact relative to business as usual. They offer two Australian case studies and in particular highlight how well the 2004 rezoning of the great barrier reef was done in terms of improving ecological representation, although still with room to improve. They suggest planners of MPAs and/or no-take zones ask four questions: 1. Are MPAs intended to protect biodiversity? 2. Do proposed MPAs give precedence to more threatened biodiversity features? 3. Do MPAs adequately represent all biodiversity features of interest? and 4. Do MPAs adequately represent variation within features (like bioregions) to focus on the most threatened sub-areas?

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. Thoughts welcome! Note that other scientists criticized the Waldron paper, noting that not nearly enough has been done to estimate how 30x30 would affect people (nor to consult with them), among other issues. The critique (Agrawal et al. 2020) is here: https://openlettertowaldronetal.wordpress.com/

Wenzel et al. 2020 (NOAA’s 2020 Marine Protected Area report) has a good overview of marine (and great lakes) protection in the U.S. 26% of US waters are in an MPA, but only 3% in a no-take zone. Page 5 of the PDF has a breakdown by region showing that some places like Alaska are disproportionately unprotected. The report also indicates MPA coverage by habitat type (e.g. 83% of mangroves are protected), calls for OECMs to improve MPA connectivity, and notes the need for better management of MPAs.


CLIMATE CHANGE:
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.

Mykleby et al. 2017 estimates how planting trees would affect climate change (both globally and locally) in Canada and the Nothern U.S. They found that in Northern Canada and some Western U.S. states, planting trees would on net warm the earth because the carbon gained is more than outweighed by covering up highly reflective snow with more absorbent tree leaves (Figure 2c). The key point here is that the impact of adding or losing trees depends a lot on location (consistent w/ Williams et al. 2021 and Betts et al. 2000), so tables w/ averages across regions (like Table 1) are not super helpful. This concern with albedo causing local warming is most significant for boreal forests, followed by temperate forests in snowy regions, and does not apply to tropical forests.

Randerson et al. 2006 is another paper looking at how boreal forest loss affects climate change. They used a 1999 boreal forest fire in Alaska as a case study, measuring not only carbon dioxide and methane, but also albedo changes (from exposing snow and ice which reflect more light, and from black carbon deposition which absorb more light) and aerosols in the burned site compared to a control site. They found that for the first ~15 years, the emissions from the fire outweigh the lower albedo and result in net warming. But after 15 years, the fire has a net cooling effect as the GHGs and black carbon and aerosols dissipate, but higher albedo persists (Fig 3b, green line).



REFERENCES:

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

Devillers, R., Pressey, R. L., Grech, A., Kittinger, J. N., Edgar, G. J., Ward, T., & Watson, R. (2015). Reinventing residual reserves in the sea: are we favouring ease of establishment over need for protection? Aquatic Conservation: Marine and Freshwater Ecosystems, 25(4), 480–504. https://doi.org/10.1002/aqc.2445

Betts, R. A. (2000). Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature, 408(6809), 187–190. https://doi.org/10.1038/35041545

Li, Y., Zhao, M., Motesharrei, S., Mu, Q., Kalnay, E., & Li, S. (2015). Local cooling and warming effects of forests based on satellite observations. Nature Communications, 6, 1–8. https://doi.org/10.1038/ncomms7603

Mykleby, P. M., Snyder, P. K., & Twine, T. E. (2017). Quantifying the trade-off between carbon sequestration and albedo in midlatitude and high-latitude North American forests. Geophysical Research Letters, 44(5), 2493–2501. https://doi.org/10.1002/2016GL071459

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.

Wenzel, L., D’Iorio, M., Wahle, C., Cid, G., Canizzo, Z., & Darr, K. (2020). Marine protected areas 2020: Building effective conservation networks. https://nmsmarineprotectedareas.blob.core.windows.net/marineprotectedareas-prod/media/docs/2020-mpa-building-effective-conservation-networks.pdf

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

Sincerely,
 
Jon

Wednesday, June 9, 2021

Some papers on 30 x 30 and protected areas in general

Lately I've been reading a lot of science papers related to protected areas and 30x30: the idea of protecting (and/or 'conserving') 30% of the earth by 2030. I thought it might be helpful to share all of the summaries I have on the topic in one place. As always, these summaries are my personal opinion only, and I welcome input / critique / etc.


Specific to recommendations for 30 x 30 in the US:

Simmons et al. 2021 (a non-peer-reviewed white paper) looks at a few options to meet 30 by 30 in the U.S. (protecting 30% of the country on land by 2030) 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).

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. 

Other papers on protection targets etc.:

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.

Bhola et al. 2020 sums up four different philosophies or perspectives for setting global conservation goals. 1) extending Aichi biodiversity target #11 (protecting & managing 17% of land and inland water, plus 10% coastal and marine, while considering biodiversity, equity, ecosystem services, and connectivity) to 2030 and ensuring the qualitative piece is achieved. 2) Big area-based goals like 'half earth' or protecting 30% of the earth by 2030 (still ensuring that the right places get protected). 3) ‘New conservation’ (broadening the tent for conservation via ecosystem services, ecotourism, and the private sector). 4) ‘Whole earth’ conservation which attacks root causes of habitat loss like inequality and economic growth (while arguing against separating people from nature). It's a quick read but start w/ Table 1 for a summary of the four perspectives, and Figure 1 which shows how the choice of goal (in this case, biodiversity vs. ecosystem service production) affects which areas you’d want to protect.

Devillers et al. 2015 argues that marine protected areas (MPAs) have largely been cited in remote areas with low threats that the MPAs are intended to address. They point out that politics drive MPAs to be established in places that minimize costs and conflicts with commercial interests, but that MPAs that avoid potential conflicts will by definition have low impact relative to business as usual. They offer two Australian case studies and in particular highlight how well the 2004 rezoning of the great barrier reef was done in terms of improving ecological representation, although still with room to improve. They suggest planners of MPAs and/or no-take zones ask four questions: 1. Are MPAs intended to protect biodiversity? 2. Do proposed MPAs give precedence to more threatened biodiversity features? 3. Do MPAs adequately represent all biodiversity features of interest? and 4. Do MPAs adequately represent variation within features (like bioregions) to focus on the most threatened sub-areas?

Hannah et al. 2020 estimates that effectively conserving 30% of tropical land could cut predicted species extinction by ~1/2-2/3 (if the conserved areas are both cited ideally and managed well: this is not about legal protection alone). Conserving 50% could reduce extinction by more like 2/3-80% (see Table 1 for details including how this varies by region). This is useful to understand how effective conservation can be at different scales. But it's important to note that citing PAs in ideal locations continues to be elusive, this model relies on fairly simple assumptions using species-area curves, and the fact that the results didn't vary much with climate change (RCP2.6 vs RCP 8.5) is concerning. Nonetheless, this could be motivating to highlight the importance of protecting and managing enough of the right places on earth to slow species extinction.

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.

Mogg et al. 2019 looks at how much protection is needed to keep land mammals healthy. They assume every species needs 80% of its range protected (plus 10% more as buffer), so Oceania and South America need more than 70% of their land to be protected! They ignore any considerations about meeting demand for food or livelihoods, and it’s odd to me to see the focus on making protected areas much larger much faster given that the paper’s intro mentions that enforcement of current PAs is a major problem. It’s definitely an interesting analysis, but I think it’s really hard to try and get support behind a proposal that doesn’t even attempt to consider human needs as well as ecosystem / species needs.

Global estimates of % protection hide the fact that protection varies widely for different ecosystems and habitat types. Sayre et al. 2020 splits that up into 278 natural ecosystems (based on temperature, moisture, elevation, land cover, etc.). If you limit protection to IUCN 1-4 (stricter protection), 9 of those 278 were totally unprotected and 206 were below 8.5% protected (halfway to Aichi targets). If you use IUCN 1-6 (including areas allowing more human use) only 1/3 of ecosystems are below 8.5%. Table 5 shows how much of each major land cover group (forests, grasslands, etc.) has been lost, Table 4 has the details for the 278 ecosystems. Some figures are easier to see online: https://www.sciencedirect.com/science/article/pii/S2351989419307231?via%3Dihub

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. Thoughts welcome! Note that other scientists criticized the Waldron paper, noting that not nearly enough has been done to estimate how 30x30 would affect people (nor to consult with them), among other issues. The critique (Agrawal et al. 2020) is here: https://openlettertowaldronetal.wordpress.com/

Wenzel et al. 2020 (NOAA’s 2020 MPA report) has a good overview of marine (and great lakes) protection in the U.S. 26% of US waters are in an MPA, but only 3% in a no-take zone. Page 5 of the PDF has a breakdown by region showing that some places like Alaska are disproportionately unprotected. The report also indicates MPA coverage by habitat type (e.g. 83% of mangroves are protected), calls for OECMs to improve MPA connectivity, and notes the need for better management of MPAs.

 

REFERENCES:

Agrawal et al. 2020. An Open Letter to the Lead Authors of ‘Protecting 30% of the Planet for Nature: Costs, Benefits and Implications.’ https://openlettertowaldronetal.wordpress.com/

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

Bhola, N., Klimmek, H., Kingston, N., Burgess, N. D., Soesbergen, A., Corrigan, C., Harrison, J., & Kok, M. T. J. (2020). Perspectives on area‐based conservation and its meaning for future biodiversity policy. Conservation Biology, 00(0), cobi.13509. https://doi.org/10.1111/cobi.13509

Devillers, R., Pressey, R. L., Grech, A., Kittinger, J. N., Edgar, G. J., Ward, T., & Watson, R. (2015). Reinventing residual reserves in the sea: are we favouring ease of establishment over need for protection? Aquatic Conservation: Marine and Freshwater Ecosystems, 25(4), 480–504. https://doi.org/10.1002/aqc.2445

Hannah, L., Roehrdanz, P. R., Marquet, P. A., Enquist, B. J., Midgley, G., Foden, W., Lovett, J. C., Corlett, R. T., Corcoran, D., Butchart, S. H. M. M., Boyle, B., Feng, X., Maitner, B., Fajardo, J., McGill, B. J., Merow, C., Morueta-Holme, N., Newman, E. A., Park, D. S., … Svenning, J. C. (2020). 30% Land Conservation and Climate Action Reduces Tropical Extinction Risk By More Than 50%. Ecography, 43(7), 943–953. https://doi.org/10.1111/ecog.05166

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. https://doi.org/10.1111/ddi.12853

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

Mogg, S., Fastre, C., Jung, M., & Visconti, P. (2019). Targeted expansion of Protected Areas to maximise the persistence of terrestrial mammals. BioRxiv, 3056, 1–22. https://doi.org/10.1101/608992

Sayre, R., Karagulle, D., Frye, C., Boucher, T., Wolff, N. H., Breyer, S., Wright, D., Martin, M., Butler, K., Van Graafeiland, K., Touval, J., Sotomayor, L., McGowan, J., Game, E. T., & Possingham, H. (2020). An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems. Global Ecology and Conservation, 21(December), e00860. https://doi.org/10.1016/j.gecco.2019.e00860

Simmons, B. A., Nolte, C., & McGowan, J. (2021). Delivering on Biden’s 2030 Conservation Commitment. https://www.bu.edu/gdp/2021/01/28/delivering-on-bidens-2030-conservation-commitment/

Waldron, A., Adams, V., Allan, J., Arnell, A., Asner, G., Atkinson, S., Baccini, A., Baillie, J. E., Balmford, A., Beau, J. A., Brander, L., Brondizio, E., Bruner, A., Burgess, N., Burkart, K., Butchart, S., Wenzel, L., D’Iorio, M., Wahle, C., Cid, G., Canizzo, Z., & Darr, K. (2020). Marine protected areas 2020: Building effective conservation networks. https://nmsmarineprotectedareas.blob.core.windows.net/marineprotectedareas-prod/media/docs/2020-mpa-building-effective-conservation-networks.pdf

Wenzel, L., D’Iorio, M., Wahle, C., Cid, G., Canizzo, Z., & Darr, K. (2020). Marine protected areas 2020: Building effective conservation networks. https://nmsmarineprotectedareas.blob.core.windows.net/marineprotectedareas-prod/media/docs/2020-mpa-building-effective-conservation-networks.pdf

Tuesday, June 1, 2021

June 2021 science summary

Come play with me

 

Hi,

Hope cicadas or other issues aren't keeping you from getting back into the world as people get vaccinated and cases are going down (in most places at least). The cicada above is super fun and ready to play!

This month I am focusing on climate change and biodiversity articles.

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon


BIODIVERSITY:

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 inhabitated 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 uninhabitated 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.

Blankenship et al. 2021 is a good overview of the best available data for historical vegetation / land cover in the U.S. (which comes from LANDFIRE's Biophysical Setting [BpS] model), and how it was produced. It estimates habitat prior to European settlement of the Americas (but not prior to the arrival of Native Americans so not free of human influence). A LOT of data and expertise went into this, including expected natural succession of diferent ecosystems after disturbance, estimated fire frequency and severity, and more. I've used it to identify which areas are appropriate to reforest and which weren't forested to begin with (so shouldn't be a target of restoration in most cases). One bonus aspect of these data is that the team who manages them are incredibly helpful and willing to provide advice and guidance on how to apply them. There is a lot of helpful detail, caveats, and next steps in here for people who may want to use these data.



CLIMATE CHANGE:

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!

Lenzen et al. 2018 estimate the global carbon footprint of tourism in 2013, and is a fascinating read but looks to me like it has some big errors. They find tourism is 8% of global emissions (much higher than other estimates, b/c they look at full supply chain emissions, which means this 8% cuts across several sectors). They helpfully summarize the results both by the countries where tourists reside, and the countries they visit (see Fig 1 and take a moment to read what it all means as it's fascinating). But some of their findings don't make sense to me. For example, they report that from 2009-2013 tourism spending went up by 88% while emissions only rose 15% (which seems very odd, and Fig SI2 on p21 of the supplement looks like spending only went up ~28%). Also, Fig 1 reports Canada as the top "net origin" by emissions but in Table 1 it seems like a huge net destination (with US travel to Canada by far the biggest flow globally). If anyone knows the paper and can point out if I'm missing something I'd appreciate it, otherwise this looks entertaining but unreliable.

Lipsett-Moore et al. 2018 finds that improved fire management in savannas could reduce a lot of greenhouse gas (GHG) emissions, especially in Africa (which has 77% of global potential, compared to 15% in South America and 8% in Austraila & PNG). The basic idea was piloted in Australia, and involves intentional burning in the early dry season to reduce fire (intensity, frequency, and scale) later on. The pilot roughly tripled the area burned early, while cutting the area burned late by 2/3, resulting in ~1/3 less GHG emissions over 7 years. This analysis uses remote sensing to estimate fire emissions and opportunities to reduce them. In South America the total emissions potential is much lower than Africa, but the relative change is larger (75% reduction). These changes count under Kyoto so can be used for carbon credits.

Milly and Dunne 2020 predict a roughly 9% decrease in flow in the Colorado River for every degree C increase in local temperature, due to evaporation increasing more than precipitation. Much of the paper is about different aspects of the model and how they corrected for some issues, but the core point that areas expecting more rain may still see rivers dry out was notable (especially in areas where snow cover is expected to decrease).


REFERENCES:

Blankenship, K., Swaty, R., Hall, K. R., Hagen, S., Pohl, K., Shlisky Hunt, A., Patton, J., Frid, L., & Smith, J. (2021). Vegetation dynamics models: a comprehensive set for natural resource assessment and planning in the United States. Ecosphere, 12(4). https://doi.org/10.1002/ecs2.3484

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

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

Lenzen, M., Sun, Y.-Y., Faturay, F., Ting, Y.-P., Geschke, A., & Malik, A. (2018). The carbon footprint of global tourism. Nature Climate Change, 8(6), 522–528. https://doi.org/10.1038/s41558-018-0141-x

Lipsett-Moore, G. J., Wolff, N. H., & Game, E. T. (2018). Emissions mitigation opportunities for savanna countries from early dry season fire management. Nature Communications, 9(1), 2247. https://doi.org/10.1038/s41467-018-04687-7

Milly, P. C. D., & Dunne, K. A. (2020). Colorado River flow dwindles as warming-driven loss of reflective snow energizes evaporation. Science, 367(6483), 1252–1255. https://doi.org/10.1126/science.aay9187


Sincerely,

 

Jon

Monday, May 3, 2021

May 2021 science summary

Leeta sitting

 Hi,


Unfortunately this is the second month in a row with a memorial dedication. Our dog (and recent office-mate) Leeta recently passed away. She was an extremely sweet 'muttweiler' who lived with us almost 13 years. She provided incredible emotional support during the pandemic, when I was dealing with harsh peer reviews on scientific papers, etc. We're struggling to adjust, so if my email replies are slow or disappointing, that's likely why.

I've just got reviews of three miscellaneous articles I read before she died (on long-distance mammal migration, forest fragmentation & degradation, and remote sensing forest canopy height).

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon

MIGRATION:
Teitelbaum et al. 2015 is an analysis of how far big herbivorous mammals migrate. They looked at 94 populations of 25 species migrating from between 10-1600 km (~6-1000 mi). The longest migrations were from caribou, onagers (a kind of Asian donkeys), and saiga antelope (figure 1). The biggest driver of migration distance was how much green vegetation was present - animals go much farther when food is sparser (table 1, figure 3). There's a nice discussion of other relevant variables, but overall they struggled to accurately model migration distance.

FORESTS:
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.

REMOTE SENSING:
Li et al. 2020 evaluates the new ICESat-2 LiDAR satellite's forest canopy height product in northeastern China, and uses machine learning applied to radar and optical satellite imagery (Sentinel-1, Sentinel-2, Landsat-8) to fill in the gaps between ICESat-2's sample points. They found ICESat-2 performed well (compared to aerial LiDAR) at moderate resolution (30-500m, with 250m performing best, and 10m and 1km performing relatively poorly). There are some issues (e.g., their aerial data was taken with deciduous leaves present, but ICESat data was taken in winter with leaves absent, and they note the correlations appear to vary by site so will always will require local calibration), but overall this confirms the utility of ICESat and offers some options for producing seamless forest canopy height maps.

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

Li, W., Niu, Z., Shang, R., Qin, Y., Wang, L., & Chen, H. (2020). High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data. International Journal of Applied Earth Observation and Geoinformation, 92(April), 102163. https://doi.org/10.1016/j.jag.2020.102163

Teitelbaum, C. S., Fagan, W. F., Fleming, C. H., Dressler, G., Calabrese, J. M., Leimgruber, P., & Mueller, T. (2015). How far to go? Determinants of migration distance in land mammals. Ecology Letters, 18(6), 545–552. https://doi.org/10.1111/ele.12435



Sincerely,
 
Jon
 
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 http://sciencejon.blogspot.com/

Thursday, April 1, 2021

April 2021 science summary

Evanston, 1990s

Greetings,

I wanted to begin this summary by acknowledging the loss of a very important person in my life. Carol Gaetjens was my biological mom's partner who played a big role in raising me (Carol was my "co-mom" or my "other mom"). She recently died suddenly and unexpectedly, and her passing leaves a big hole in my heart. Here's her obituary for those who are interested.

Among the many things she taught me was to rethink my assumptions age and the elderly (through her work as a gerontologist). So I wanted to include an article she wrote about the perceptions of gerontology students on age diversity in the classroom in this month's summary.

I also wanted to thank her for more recently inspiring me to write a much shorter version of my last research article. When I sent her the full paper, she said she loved it, but wanted "a short version that I could pass out to my students that they'd actually read. You know, get to the good stuff without all that academic citation bullshit!" That kind of enthusiasm paired with clear and useful feedback was a hallmark of Carol's. When I sent her a draft of the short version, she liked it, but also griped about all of the other stuff in the full article she missed, before we concluded that maybe there was no perfect length of a summary.

Unrelated to that, I just had a couple of blogs about learning from failure published (after we failed to get it published at the first place we tried, appropriately enough). The first one summarizes barriers to learning from failure, and the second one has suggestions to make learning from failure easier and more productive.

I've also got a couple more articles about protected areas that people sent me in response to the March science summary I sent.

If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon


GERONTOLOGY:
Gaetjens 1997 is a really interesting read about how gerontology students think about the value of age diversity in their programs. Unlike virtually any other program, in gerontology students vary widely in age (in Carol's sample from Northeastern University where she taught, students in the program ranged from 23 to 77. The paper is a pretty quick and easy read (let me know if you want a copy), but in short it covers their attitudes about the age diversity in the program, and if / how age should be used as a criteria for being accepted into the program and/or for financial aid. She found that most students spoke very positively about the value of age diversity, but a few middle aged and older students thought that people younger than 25 or 30 might not be mature enough to study aging, and that people over 70 may have cognitive issues that would frustrate them. She concluded that gerontology faculty had a key role to play in helping their students identify their ageist beliefs, and to work on reducing their bias through their studies.


PROTECTED AREAS:
Wolf et al. 2021 looks at how well protected areas (PAs) are reducing deforestation (compared to unprotected areas). Some PAs are in places where deforestation isn't happening regardless of protection, and other PAs are losing forests despite protection; neither kind helps conservation much (although the former may be useful if deforestation patterns shift and those PAs are enforced). They found PAs lost 41% less tree cover than similar unprotected areas. I'm not convinced that is an accurate number, but the important thing is that they found PAs are slowing deforestation but still losing a lot of trees. This shows the limits of a quantitative goal like 30 by 30 if it doesn't include a qualitative aspect including efficacy. PAs lost more tree cover when they were large and/or in regions with more deforestation overall. Fig 5 highlights countries with the most forest vertebrate species and the lowest forest protection. Note that this study looks at 'tree cover loss' rather than deforestation as land use change; some of the lost trees may be due to natural events or sustainable timber harvest that will allow the forest to regrow (as opposed to being permanently changed from forest to non-forest). This is important as tree cover loss in protected areas in countries like the U.S. is usually legal since some types of protection allow for timber harvest or other extractive uses.

Mogg et al. 2021 (a preprint, not yet peer reviewed) is an interesting global analysis of what protected areas (PAs) would be needed to minimize extinction risk of land mammals (by ensuring all species have 80% of their range protected and other IUCN Red List criteria). Unsurprisingly they find we would need a lot more protection: 60% of all land outside Antarctica, and >70% in Oceania and South America would have to be protected. But this analysis is solely driven by the needs of wildlife, and ignores the projected human need for food and livelihoods. In fact, they focus on areas suitable for agriculture (given the higher conversion threat) which makes it likely their recommended scenario would be unable to keep up with human demand for food. They also ignore capacity and resources needed for enforcement, which is already an issue, and would be much harder with a rapid expansion of PAs focusing on areas currently being converted. As a result, I imagine this analysis is non-convincing to anyone who isn't already strongly supportive of conservation as a top priority.


ECOLOGY:
Bergstrom et al. 2021 assesses 19 ecosystems in Australia (2 fresh, 4 marine, 13 terrestrial), finding that all either have collapsed or are collapsing (on at least a local scale). Their definition of collapse is pretty broad: a documented transition to a new ecosystem state over >10 years, along with any substantial changes in: population size or keystone or characteristic species, ecosystem biomass, ecosystem engineers, or ecosystem services / functions (they consider the latter to be evidence that recovery is unlikely). They offer detailed information about each ecosystem in the supplement, and note that for collapsed ecosystems, the only options are accept the collapse, "renovate" the ecosystem to intentionally modify some elements to allow recovery, or "adapt" to a novel or highly modified ecosystem.

Provencher et al. 2020 makes a case that in prioritizing where to focus conservation effort, we should consider "biodiversity potential." This is partly about ecosystem condition or how many species are present relative to their potential maximum number of species, partly about threats that reduce that maximum potential, and partly about irreplaceability of the species and systems present. They use greasewood shrublands which live on salty soils as a case study; overall species richness is low but they still serve important functions. They note that groundwater withdrawals are a key threat that reduces the biodiversity potential of greasewood ecosystems, and call for more work on these and other undervalued ecosystems.


REFERENCES:

Bergstrom, D. M., Wienecke, B. C., Hoff, J., Hughes, L., Lindenmayer, D. B., Ainsworth, T. D., Baker, C. M., Bland, L., Bowman, D. M. J. S., Brooks, S. T., Canadell, J. G., Constable, A. J., Dafforn, K. A., Depledge, M. H., Dickson, C. R., Duke, N. C., Helmstedt, K. J., Holz, A., Johnson, C. R., … Shaw, J. D. (2021). Combating ecosystem collapse from the tropics to the Antarctic. Global Change Biology, October 2020, gcb.15539. https://doi.org/10.1111/gcb.15539

Gaetjens, C. A. (1997). Contributions of age diversity among students to graduate education in gerontology: Students’ view. In Educational Gerontology (Vol. 23, Issue 8, pp. 763–774). https://doi.org/10.1080/0360127970230802

Mogg, S., Fastre, C., Jung, M., & Visconti, P. (2019). Targeted expansion of Protected Areas to maximise the persistence of terrestrial mammals. BioRxiv, 3056, 1–22. https://doi.org/10.1101/608992

Provencher, L., Saito, L., Badik, K., & Byer, S. (2020). All systems are equal: In defense of undervalued ecosystems. Rangelands, 42(5), 159–167. https://doi.org/10.1016/j.rala.2020.07.002

Wolf, C., Levi, T., Ripple, W. J., Zárrate-Charry, D. A., & Betts, M. G. (2021). A forest loss report card for the world’s protected areas. Nature Ecology & Evolution. https://doi.org/10.1038/s41559-021-01389-0

Sincerely,
 
Jon

p.s. for my American readers, nothing in this summary is an April Fools' Joke. I don't mess around when it comes to science.