“Protecting 50 % of Earth’s Surface Area”: the CBD’s Equivalent Goal to the UNFCCC’s Target of “Limiting Surface Temperature Rise to 2 Degrees”

Source: Dinerstein et al., 2017

I thought Edward O. Wilson was the first person who called for protecting half of the global terrestrial area in order to avoid catastrophic mass extinctions. Now, however, I learned the “Half-Earth” (Wilson, 2016) or “Nature Needs Half” (Locke, 2013) slogans have a decades-long robust scientific consensus among conservation biologists, dating back to Odum brothers’ 1972 paper. This month, a group of scientists published a comprehensive review paper (Dinerstein et al., 2017) in BioScience along with online thematic maps of 864 ecoregions distributed among the Earth’s 14 terrestrial biomes at http://ecoregions2017.appspot.com/.

For this paper, the authors have updated the famous 2001 ecoregions map. Then they assessed the extent of both protected areas and remaining natural habitat withing each (forested and nonforested) ecoregion. Previously, about 15 % of global land was known to be protected. According to this new analysis, only 12 % of the terrestrial biosphere (13 % of forested biomes and 10 % of nonforested biomes) is protected. So the authors suggest that the global efforts increase the amount of land under formal protection by 8 to 10 % per decade, while the current increase rate is 4 % per decade.

So, I think the Convention on Biological Diversity can set the “Half-Earth” as a tentative global goal that is its equivalent target to the UNFCCC’s goal of limiting global warming under 2 degrees Celsius from pre-industrial global average surface temperature. Of course, when the IPBES’s global assessment on biodiversity and ecosystem services is published in 2019 (2nd quarter), the official global target endorsed by policymakers might become stricter, just as the Paris Agreement called for limiting the temperature increase to “below 1.5 degrees Celsius” above pre-industrial levels, even further than IPCC’s previous recommendation of 2 degrees-warming.

References:

Dinerstein, E., et al. (2017). An Ecoregion-Based Approach to Protecting Half the Terrestrial Realm. BioScience, 67(6), 534–545. [Full-text at http://doi.org/10.1093/biosci/bix014]

Locke, H. (2013). Nature Needs Half: A Necessary and Hopeful New Agenda for Protected Areas. Parks, 19(2), 9–18. [Full-text at http://j.mp/Locke2013]

Odum, E. D., & Odum, H. T. (1972). Natural Areas as Necessary Components of Man’s Total Environment. In Transactions of the North American Wildlife and Natural Resources Conference (pp. 178–189). Washington, DC: Wildlife Management Institute.

Wilson, E. O. (2016). Half-Earth: Our Planet’s Fight for Life. New York, NY: Liveright.

Analytical Conceptual Frameworks of IPBES: An Update

This is a minor update of my previous (June 2014) post (“Analytical Conceptual Frameworks of IPBES”) at http://j.mp/IPBES. There was a small change from the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES).

The “Nature’s Benefits to People,” a key component of the IPBES’s analytical conceptual frameworks, was renamed to “Nature’s Contributions to People” (NCP) by the October 2016 decision of the platform’s Multidisciplinary Expert Panel (MEP) for the following two reasons (see IPBES/5/INF/24):

1. The word “benefits”, with its strongly positive connotation, wrongly conveyed the idea that negative contributions from nature towards peoples’ good quality of life would be excluded.
2. The different meanings of the word “benefits” in common speech in different languages as well as in the social sciences and the valuation literature represented potential sources of confusion. 

Therefore, NCP represents of two contributions that people obtain from nature (Pascual et al., 2017):

1. All the positive contributions or benefits
2. Occasionally negative contributions, losses or detriments

So, I have updated the Analytical Conceptual Frameworks of IPBES. Please note that “only images and web-links” are updated. All the remaining are the same.

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Analytical Conceptual Frameworks of IPBES: An Update

Now the IPCC's Fifth Assessment Reports (a.k.a. AR5) are all released except the Synthesis part. There is a relatively new IPCC-like intergovernmental organization focusing on biodiversity and ecosystem services.
The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, or IPBES, has launched in 2012.
I welcome this new organization wholeheartedly. See, the title of my blog is "Energy and Ecology." If the IPCC is more about energy (as a means of climate change mitigation), the IPBES is more about ecology.
Just as the IPCC has done to connect science and policy since the publication of the First Assessment Report (FAR) in 1990, the IPBES is planning to generate timely assessment reports regularly for the world's policymakers. The first global assessment of the IPBES is scheduled to be published by 2018 and will replace the Millennium Ecosystem Assessment (published by WRI, UNEP, the World Bank, and UNDP in 2005) as the most authoritative report on the status of the Earth's biomes and ecosystems.
The following figures are a beautified version of the IPBES's analytical conceptual framework and operational conceptual model drawn by the Platform's experts at the 2013 IPBES's second Plenary (IPBES-2). These figures will provide a basis of future IPBES studies. In the analytical framework (Figure 1), there are six building-blocks and two big arrows representing spatial and temporal scales each. The operational model (Figure 2) explains how science and policy interacts with each other through the IPBES processes, while the analytical framework supports the four functions of the IPBES – knowledge generation, assessments, policy support tools and methodologies, and capacity-building.
These figures appear to be influenced by the conceptual framework of the United Kingdom's 2011 National Ecosystem Assessment (2011) as well as that of the United Nations Millennium Ecosystem Assessment (2005). Interestingly, the IPBES analytical conceptual framework has made the UK NEA framework updated as manifested in its follow-on phase report (2014) (Figure 3). A detailed explanation of Figures 1 and 2 can be found in the IPBES-2 report (2014) and could be compared with the conceptual framework of the Millennium Ecosystem Assessment.

Figure 1. IPBES Analytical Conceptual Framework
(vector [emf] image: http://j.mp/IPBES-ACF)

Source: My drawing based on IPBES-5.


Figure 2. Operational Conceptual Model of the IPBES
(vector [emf] image: http://j.mp/IPBES-OCM)


Source: My drawing based on IPBES-5.

Figure 3. UK NEA Follow-on Phase Ecosystem Services Conceptual Framework

Source: My drawing based on UK NEA FO.

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Reference: Pascual, U., Balvanera, P., Díaz, S., Pataki, G., Roth, E., Stenseke, M., . . . Yagi, N. (2017). Valuing nature’s contributions to people: the IPBES approach. Current Opinion in Environmental Sustainability, 26–27, 7–16. doi:10.1016/j.cosust.2016.12.006

Cost of Energy Comparison, Including Levelized Cost of Energy (LCOE)—2017 Update

I updated the list in a new post for the year of 2018. Please move to the post cited below. Park, H. (2018). Cost of Energy Comparison, Including Levelized Cost of Energy (LCOE)—2018 Update [Blog post]. Retrieved from http://j.mp/LCOE_2018

In 2025, Onshore Wind and Large-Scale Solar Will Outperform Nuclear

According to the UK’s Department of Energy & Climate Change (DECC), the estimated future costs (in 2025) of onshore wind and large-scale solar power will be more competitive than that of nuclear power. As we can obviously notice, DECC's estimates for the same year were quite different just 3 or 6 years ago. It is good news for those countries who have to greatly increase the shares of low-carbon energy sources to satisfy the mitigation pledges manifested in their Intended Nationally Determined Contributions (INDCs; or now, their first Nationally Determined Contributions [NDCs]).

Note: If you want to know the current cost estimates of different energy technologies, please read my previous post (“Cost of Energy Comparison, Including Levelized Cost of Energy (LCOE) - 2016 Update” at http://j.mp/LCOE_2016).

Figure: Levelized cost of generating 1 MWh with different technologies in 2025: changes in DECC’s estimates



Source: National Audit Office. (2016). Nuclear Power in the UK. London, UK: National Audit Office. [Full-text at http://j.mp/2016_UK_LCOE]

$/£ Exchange Rate in 2014: 1 pound sterling = $1.6484 (Source: https://fred.stlouisfed.org/series/AEXUSUK)

Cost of Energy Comparison, Including Levelized Cost of Energy (LCOE) - 2016 Update

I updated the list in a new post for the year of 2017. Please move to the post cited below. Park, H. (2017). Cost of Energy Comparison, Including Levelized Cost of Energy (LCOE)—2017 Update [Blog post]. Retrieved from http://j.mp/LCOE_2017

Suicide Rates in Old Age: An International Comparison

I have compared elderly suicide rates among 34 countries. As we can easily observe from the figure below, South Korea’s elderly suicide rates are a big problem in the country.
In Korea, among 100,000 people who are 75 years old and over, 109 people committed suicide in 2009. The second-highest suicide rate in this comparison (42/100,000 in Hungary) is less than half of the tragic number.


Source: WHO (2014)
Note: All data (‘number of deaths’ and ‘age group population’) are from 2009, except Canada (2005) and United States of America (2007).


South Korea’s high suicide rates among elders might be partially caused by their poverty. Among OECD countries, South Korean elders suffer the most from destitution.
Source: OECD (2015)
Note: All data are from 2013 or most recent year.

References:

Organisation for Economic Co-operation and Development. (2015). Pensions at a Glance 2015: OECD and G20 Indicators. Paris, France: OECD Publishing. [Full-text at http://j.mp/OECD_Pensions_2015]

World Health Organization. (2014). WHO Mortality Database. Geneva, Switzerland: World Health Organization. [Data at http://apps.who.int/healthinfo/statistics/mortality/whodpms/]

Life Expectancy and Energy Consumption: Countries and U.S. States - an Update

All of a sudden, I wanted to update my old post with the latest data. So I did using the year 2010 data. Below, I'm presenting a summary plot first, and then you can find the data table.
In general, as you can easily observe from the figure, longer-living people consume more energy. However, the U.S. states look different. The slope of the trend line is negative in the United States.

Life Expectancy and Energy Use: Countries and U.S. States
(All data are from the year 2010.)


Data table:

Country / State	Life expectancy at birth (years)	Energy use (tonnes of oil equivalent per capita)
Hong Kong SAR, China	82.98	4.855
Japan	82.84	4.305
Switzerland	82.25	4.272
Italy	82.04	3.178
Iceland	81.90	17.354
Australia	81.70	6.962
France	81.66	4.278
Spain	81.63	3.383
Israel	81.60	3.269
Singapore	81.54	14.084
Sweden	81.45	6.113
Malta	81.40	6.489
Hawaii	81.30	5.065
Minnesota	81.05	8.820
Norway	81.00	9.928
Canada	80.89	9.692
Connecticut	80.82	5.342
California	80.77	5.267
Ireland	80.74	3.464
Netherlands	80.70	6.491
New Zealand	80.70	5.122
Faroe Islands	80.64	5.597
Luxembourg	80.63	10.016
Austria	80.58	4.681
Korea, South	80.55	5.608
Massachusetts	80.52	5.418
New York	80.48	4.813
Vermont	80.45	6.023
United Kingdom	80.40	3.605
Greece	80.39	3.164
New Hampshire	80.32	5.594
New Jersey	80.28	6.879
Belgium	80.23	6.866
Utah	80.20	6.854
Colorado	80.02	7.535
Germany	79.99	4.328
Wisconsin	79.98	7.913
Washington	79.92	7.610
Finland	79.87	6.223
Rhode Island	79.87	4.561
Nebraska	79.84	11.819
Iowa	79.71	12.323
Macao SAR, China	79.69	1.293
Arizona	79.64	5.418
North Dakota	79.55	17.741
Oregon	79.52	6.426
Idaho	79.49	8.316
South Dakota	79.47	11.642
Florida	79.45	5.720
Slovenia	79.42	3.914
Cyprus	79.31	2.777
Bermuda	79.29	3.571
Costa Rica	79.28	1.044
Lebanon	79.25	1.667
Maine	79.19	7.812
Taiwan	79.18	5.352
Denmark	79.10	3.786
Chile	79.05	1.987
Portugal	79.03	2.623
Virginia	79.01	7.787
Illinois	78.96	7.761
Maryland	78.80	6.401
Kansas	78.72	10.256
Cuba	78.72	0.908
United States	78.54	7.942
Pennsylvania	78.50	7.434
Montana	78.49	10.055
Texas	78.45	11.894
New Mexico	78.43	8.114
Delaware	78.36	7.056
Wyoming	78.34	23.940
Alaska	78.29	22.629
Michigan	78.23	7.031
Puerto Rico	78.18	2.543
Qatar	78.15	18.623
Guam	78.10	5.682
Nevada	78.05	5.997
Brunei	77.99	9.397
North Carolina	77.81	7.081
Ohio	77.75	8.391
Indiana	77.61	11.163
Missouri	77.54	8.089
New Caledonia	77.47	4.221
Czech Republic	77.42	3.955
Georgia	77.23	8.039
Albania	76.98	1.067
South Carolina	76.95	8.921
Panama	76.95	2.180
Maldives	76.79	0.929
Mexico	76.69	1.634
Uruguay	76.62	1.586
United Arab Emirates	76.60	18.121
District of Columbia	76.53	7.761
Croatia	76.48	2.194
Tennessee	76.30	8.946
Bahrain	76.26	11.793
Poland	76.25	2.653
Oman	76.05	8.040
Kentucky	75.97	11.441
Arkansas	75.96	9.601
Oklahoma	75.88	10.584
Bosnia and Herzegovina	75.81	2.200
Louisiana	75.71	22.604
French Polynesia	75.69	1.676
Argentina	75.66	2.156
Ecuador	75.65	1.014
Estonia	75.43	1.579
Alabama	75.42	10.256
West Virginia	75.40	9.979
Antigua and Barbuda	75.33	2.956
Vietnam	75.31	0.570
Slovakia	75.11	3.543
Saudi Arabia	75.08	8.148
Mississippi	74.96	10.029
Aruba	74.95	3.699
China	74.89	1.798
Syria	74.87	1.152
Barbados	74.80	1.703
Libya	74.79	3.867
Macedonia	74.72	1.519
Tunisia	74.60	0.740
Bahamas, The	74.59	3.951
Malaysia	74.50	2.709
Montenegro	74.42	2.061
Saint Lucia	74.41	0.960
Serbia	74.34	2.434
Armenia	74.22	1.111
Turkey	74.21	1.454
Hungary	74.21	2.656
Venezuela	74.17	2.988
Kuwait	74.16	13.257
Peru	73.91	0.767
Cape Verde	73.86	0.273
Thailand	73.81	1.704
Nicaragua	73.80	0.325
Sri Lanka	73.76	0.291
Georgia	73.67	1.054
Bulgaria	73.51	2.607
Latvia	73.48	1.939
Romania	73.46	1.625
Jordan	73.44	1.269
Colombia	73.37	0.783
Belize	73.27	0.960
Lithuania	73.27	1.831
Seychelles	73.20	4.121
Iran	73.13	3.021
Brazil	73.08	1.475
Mauritius	72.97	1.399
Honduras	72.85	0.418
Jamaica	72.85	1.000
Dominican Republic	72.79	0.742
Palestinian Territories (West Bank and Gaza)	72.64	0.299
Samoa	72.41	0.375
Grenada	72.34	0.927
Saint Vincent and the Grenadines	72.18	0.785
Tonga	72.18	0.602
Paraguay	72.03	1.729
El Salvador	71.63	0.519
Guatemala	71.00	0.396
Vanuatu	70.84	0.182
Greenland	70.84	6.004
Cambodia	70.64	0.107
Algeria	70.62	1.312
Egypt	70.45	1.017
Azerbaijan	70.45	1.561
Belarus	70.40	2.940
Suriname	70.34	2.028
Ukraine	70.27	2.801
Morocco	70.17	0.582
Indonesia	70.17	0.649
Kosovo	69.90	1.484
Trinidad and Tobago	69.60	19.358
Bangladesh	69.49	0.153
Fiji	69.38	0.674
Kyrgyzstan	69.30	0.940
Korea, North	68.90	0.850
Russia	68.86	5.309
Iraq	68.83	1.298
Moldova	68.46	0.819
Kazakhstan	68.30	3.452
Philippines	68.23	0.307
Kiribati	67.88	0.220
Uzbekistan	67.86	1.781
Nepal	67.10	0.073
Solomon Islands	67.07	0.138
Bhutan	67.00	2.076
Tajikistan	67.00	0.654
Laos	66.90	0.293
Mongolia	66.89	0.792
Bolivia	66.32	0.615
Pakistan	66.13	0.357
Timor-Leste (East Timor)	65.94	0.061
Sao Tome and Principe	65.85	0.275
India	65.69	0.491
Turkmenistan	65.02	5.059
Burma (Myanmar)	64.58	0.114
Madagascar	63.35	0.040
Senegal	62.84	0.187
Yemen	62.53	0.389
Namibia	62.48	0.747
Gabon	62.29	0.812
Rwanda	62.21	0.028
Papua New Guinea	62.01	0.243
Haiti	61.87	0.081
Ethiopia	61.47	0.040
Eritrea	61.19	0.042
Mauritania	61.02	0.219
Ghana	60.60	0.208
Djibouti	60.29	0.567
Comoros	60.20	0.066
Sudan and South Sudan	59.73	0.177
Afghanistan	59.60	0.106
Kenya	59.55	0.138
Liberia	59.43	0.052
Tanzania	59.18	0.069
Benin	58.75	0.205
Gambia, The	58.13	0.097
Uganda	57.30	0.050
Congo (Brazzaville)	57.20	0.445
Niger	56.99	0.031
Togo	55.47	0.138
Guinea	55.30	0.059
Burkina Faso	55.01	0.042
Zambia	54.53	0.260
South Africa	54.39	2.910
Somalia	54.02	0.030
Mali	53.77	0.021
Cameroon	53.69	0.163
Zimbabwe	53.59	0.348
Guinea-Bissau	53.56	0.090
Malawi	53.47	0.050
Burundi	52.62	0.012
Equatorial Guinea	51.53	2.638
Nigeria	51.29	0.126
Angola	50.65	0.422
Chad	49.77	0.009
Côte d'Ivoire (Ivory Coast)	49.68	0.147
Mozambique	49.14	0.208
Congo (Kinshasa)	48.99	0.042
Swaziland	48.35	0.340
Central African Republic	48.10	0.032
Lesotho	47.48	0.199
Botswana	46.44	0.923
Sierra Leone	44.84	0.050

Sources:

Energy Information Administration. (2015). International Energy Statistics. Washington, DC: Energy Information Administration. [Data at http://j.mp/TETPB_Countries]

Energy Information Administration. (2015). State Energy Data System (SEDS): 1960-2013 (Complete). Washington, DC: Energy Information Administration. [Data at http://j.mp/EIA_SEDS]

Lewis, K., & Burd-Sharps, S. (2013). The Measure of America 2013-2014. New York, NY: Measure of America. [Full-text at http://www.measureofamerica.org/measure_of_america2013-2014/]

Ministry of the Interior, R.O.C. (2014). Life Tables for Republic of China. Taipei, Taiwan: Ministry of the Interior, R.O.C. [Data at http://j.mp/Taiwan_LE]

World Bank. (2015). Life expectancy at birth, total (years). Washington, DC: The World Bank. [Data at http://j.mp/WB_LE]