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

June 2021 science summary

 

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