clearly shows the abrupt collapse in just thirty years<fnref n="199" />. On July 2, 1992, the Canadian government announced a moratorium on cod fishing. Originally intended to be a temporary two-year ban to allow the northern cod population to recover, the moratorium has effectively become permanent, as cod stocks have shown very limited signs of recovery even after more than 30 years. This decision had a devastating impact on coastal communities that depended on the fishery, resulting in the loss of approximately 30 000 jobs — one of the largest mass layoffs in Canadian history. Other notable examples of fishery collapses and management challenges include the Californian Pacific sardine collapse (which reached its lowest point in the mid-1950s), the Peruvian anchoveta crisis (1972-1973, triggered by an El Niño event combined with overfishing), the overexploitation of orange roughy (beginning in the 1980s, particularly severe in New Zealand and Australia), the significant decline of Pacific bluefin tuna (throughout the 20th century), and the Namibian sardine collapse (late 1960s to early 1970s). In some cases, however, these species have shown signs of recovery.

<figure><img src="image_253.png" /><figcaption>Figure 5.100: Global seafood production in Mt (1960-2022)</figcaption></figure>

Source: https://databank.worldbank.org/source/world-development-indicators & Author's calculations.

To better understand the current sustainability of fisheries in the world, we refer to the FAO report on world fisheries and aquaculture. According to FAO (2024b), fish production (including algae production) reached a new record high, with a total production<fnref n="200" /> of 223.2 million tonnes (Figure 5.100). Of this production, 89% is used for human consumption, equivalent to an estimated 20.7 kg

$$x(t+1) = x(t) + \delta x(t) \left(1 - \frac{x(t)}{\kappa}\right) - h(t)$$

where $x(t)$ is the biomass stock in year $t$, $\delta$ is the intrinsic growth rate, $\kappa$ is the carrying capacity and $h(t)$ is the fish harvest in year $t$.

<footnote n="199">¹⁹⁹The biomass stock is estimated using the discrete version of the logistic growth population model with harvest:</footnote>

<footnote n="200">²⁰⁰63% of this production is finfish, 17% algae, 11% molluscs and 8% crustaceans.</footnote>
per capita, while the remainder is mainly used for fishmeal and fish oil. The FAO estimates that 61.8 million people are employed in the primary production sector. In sixty years, fish production has increased by a factor of more than 5, while the growth rate between 1960 and 2022 is 2.98%. These figures can be explained by two factors: an increase in the world's population and an increase in the share of seafood in the human diet.

<figure><img src="image_254.png" /><figcaption>Figure 5.101: Global capture fisheries and aquaculture in Mt (1960–2022)</figcaption></figure>

Source: https://databank.worldbank.org/source/world-development-indicators & Author's calculations.

An annual growth rate of 3% means a multiplication factor of 19 over one century and 369 over two centuries! In this context, it is understandable that some people predict that sooner or later the oceans will be empty. However, if we examine the components of the production, namely capture fisheries and aquaculture<fnref n="201" />, we observe two distinct phases (Figure 5.101):

* From 1960 to 1990, production growth was driven primarily by capture fisheries.

* Since 1990, capture fisheries have remained constant, while aquaculture has experienced impressive growth.

In 1960, capture fisheries accounted for 95% of seafood production, while today aquaculture contributes about 60% of total seafood production. As a result, fish production has shifted from an industry based on the capture of wild fish to one based on aquaculture. Table 5.65 shows seafood

<footnote n="201">²⁰¹Here are the definitions used by the FAO. Capture fisheries production measures the volume of fish catches landed by a country for all commercial, industrial, recreational and subsistence purposes. Aquaculture is understood to mean the farming of aquatic organisms including fish, molluscs, crustaceans and aquatic plants. Aquaculture production specifically refers to output from aquaculture activities, which are designated for final harvest for consumption. Total fisheries production measures the volume of aquatic species caught by a country for all commercial, industrial, recreational and subsistence purposes. The harvest from mariculture, aquaculture and other kinds of fish farming is also included.</footnote>
<table><caption>Table 5.65: Fisheries production by country (1960–2022)</caption><thead><tr><th>Country</th><th>1960</th><th>1980</th><th>2000</th><th>2010</th><th>2020</th><th>2022</th></tr></thead><tbody><tr><td colspan="7">Capture fisheries production</td></tr><tr><td>World (in Mt)</td><td>31.6</td><td>58.1</td><td>94.1</td><td>87.7</td><td>90.3</td><td>88.0</td></tr><tr><td>China</td><td>7.0</td><td>5.4</td><td>15.8</td><td>17.2</td><td>14.9</td><td>15.0</td></tr><tr><td>Indonesia</td><td>2.2</td><td>2.8</td><td>4.4</td><td>6.1</td><td>7.7</td><td>8.4</td></tr><tr><td>India</td><td>3.5</td><td>3.6</td><td>4.0</td><td>5.4</td><td>5.2</td><td>6.3</td></tr><tr><td>Peru</td><td>11.1</td><td>4.7</td><td>11.3</td><td>4.9</td><td>6.3</td><td>6.1</td></tr><tr><td>Russia</td><td>0.0</td><td>0.0</td><td>4.3</td><td>4.6</td><td>5.6</td><td>5.7</td></tr><tr><td>United States</td><td>8.6</td><td>6.4</td><td>5.1</td><td>5.0</td><td>4.7</td><td>4.8</td></tr><tr><td>Vietnam</td><td>1.4</td><td>0.8</td><td>1.7</td><td>2.6</td><td>3.9</td><td>4.1</td></tr><tr><td>Japan</td><td>18.7</td><td>17.3</td><td>5.5</td><td>4.8</td><td>3.6</td><td>3.4</td></tr><tr><td>Chile</td><td>1.1</td><td>5.0</td><td>4.8</td><td>3.5</td><td>2.4</td><td>3.1</td></tr><tr><td>Norway</td><td>4.4</td><td>4.4</td><td>3.1</td><td>3.2</td><td>2.9</td><td>3.0</td></tr><tr><td colspan="7">Aquaculture production</td></tr><tr><td>World (in Mt)</td><td>2.0</td><td>7.6</td><td>43.0</td><td>78.0</td><td>122.8</td><td>126.9</td></tr><tr><td>China</td><td>46.8</td><td>40.8</td><td>69.2</td><td>61.3</td><td>57.4</td><td>59.4</td></tr><tr><td>Indonesia</td><td>3.9</td><td>3.0</td><td>2.3</td><td>8.0</td><td>12.1</td><td>11.5</td></tr><tr><td>India</td><td>2.2</td><td>4.8</td><td>4.5</td><td>4.9</td><td>7.0</td><td>8.1</td></tr><tr><td>Vietnam</td><td>1.8</td><td>1.3</td><td>1.2</td><td>3.5</td><td>3.8</td><td>4.1</td></tr><tr><td>Bangladesh</td><td>2.4</td><td>1.2</td><td>1.5</td><td>1.7</td><td>2.1</td><td>2.2</td></tr><tr><td>Philippines</td><td>3.0</td><td>4.4</td><td>2.6</td><td>3.3</td><td>1.9</td><td>1.9</td></tr><tr><td>Norway</td><td>0.1</td><td>0.1</td><td>1.1</td><td>1.3</td><td>1.2</td><td>1.3</td></tr><tr><td>Egypt</td><td>0.2</td><td>0.2</td><td>0.8</td><td>1.2</td><td>1.3</td><td>1.2</td></tr><tr><td>Chile</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.9</td><td>1.2</td><td>1.2</td></tr><tr><td>Myanmar</td><td>0.0</td><td>0.0</td><td>0.2</td><td>1.1</td><td>0.9</td><td>0.9</td></tr><tr><td colspan="7">Total production</td></tr><tr><td>World (in Mt)</td><td>33.6</td><td>65.5</td><td>136.7</td><td>165.0</td><td>211.9</td><td>213.6</td></tr></tbody></table>

Source: https://databank.worldbank.org/source/world-development-indicators & Author's calculations.

production by country across different decades<fnref n="202" />. In 1960, fish production was led by Japan, Peru, China, and the United States, with production shares of 18.6%, 10.4%, 9.5%, and 8.4%, respectively. These countries were followed by Norway (4.1%), India (3.5%), the United Kingdom (3.0%), Canada (2.8%), Spain (2.7%), South Africa (2.6%), Germany (2.3%), France (2.3%), Indonesia (2.3%), and Iceland (1.9%). In 2022, seafood production had become dominated by China with a production share of 41.5%, followed by Indonesia (10.3%), India (7.4%), Vietnam (4.1%), Peru (2.6%), Russia (2.5%), Bangladesh (2.2%), the United States (2.2%), Norway (2.0%), and Chile (2.0%). This represents a complete transformation of global seafood production over sixty years. For example, in 2022, former major producers had dropped significantly in rank: Japan (13th, 1.83%), Spain (23rd, 0.51%), Canada (25th, 0.41%), France (30th, 0.34%), and Germany (54th, 0.10%). Today, 70% of production is located in Asia, while South America, Europe, Africa and North America represent 9%, 9%, 7% and 3%, respectively. We also observe a long-term upward trend in per capita consumption of aquatic food products. Between 1961 and 2021, consumption rises from 9.1 kg to 20.6 kg per person, an average annual increase of about 1.4%. The growth in fish production can then be attributed equally to demographic expansion and changes in dietary preferences.

<footnote n="202">²⁰²These figures differ from previous ones because they exclude some forms of algae production.</footnote>
FAO (2024b) assesses the sustainability of fisheries by comparing the biomass stock $x(t)$ with the maximum sustainable yield (MSY) and defines three categories:

<table><thead><tr><th>Category</th><th>Overfished</th><th>Maximally sustainably fished</th><th>Underfished</th></tr></thead><tbody><tr><td>x(t)/MSY</td><td>[0, 0.8[</td><td>[0.8, 1.2]</td><td>]1.2, +∞)</td></tr><tr><td>Unsustainable</td><td>✓</td><td></td><td></td></tr><tr><td>Sustainable</td><td></td><td>✓</td><td>✓</td></tr></tbody></table>

The FAO analysis shows that the proportion of fishery stocks within biologically sustainable levels declined from 94% in 1974 to 62% in 2021²⁰³. This means that 38% of fishery stocks are not sustainable. This figure masks a large discrepancy between the 15 major FAO fishing regions<fnref n="204" />. Indeed, four areas have more than 50% of their fish stocks at unsustainable levels: the eastern central Atlantic (51.3%), the northwest Pacific (56%), the Mediterranean and Black Sea (62.5%), and the southeast Pacific (66.7%). In contrast, four areas have more than 75% of fisheries stocks that are sustainable: the eastern central Pacific (84.2%), the northeast Atlantic (79.4%), the northeast Pacific (76.5%), and the southwest Pacific (75.9%). According to FAO (2024b, Figure 20, page 45), three distinct patterns emerge:

1. Areas with a continuously increasing trend in landings since 1950

This group includes four areas: the eastern central Atlantic, the eastern and western Indian Ocean, and the western central Pacific.

2. Areas with landings oscillating around a globally stable value since 1990, associated with the dominance of pelagic, short-lived species

This group includes three areas: the northwest, northeast and eastern central Pacific.

3. Areas with an overall declining landing trend following historical peaks

This group includes the remaining eight regions.

With fisheries production expected to increase by 10% over the next decade, FAO has proposed a process to achieve this goal and improve sustainability: the *FAO Blue Transformation Roadmap 2022–2030*. This roadmap focuses on three main pillars: expanding sustainable aquaculture, improving fisheries management, and strengthening value chains and market access (FAO, 2022). Since we have reached a limit in terms of harvesting wild fish, the growth of fisheries production would be mainly through aquaculture. It is also important to improve fisheries management. For example, there is an urgent need to reduce discards or bycatch:

> "Discards, or discarded catch is that portion of the total organic material of animal origin in the catch, which is thrown away, or dumped at sea for whatever reason. It does not include plant materials and post-harvest waste such as offal. The discards may be dead, or alive." (Pérez Roda et al., 2019, page 1).

This happens for various reasons, such as the fish are too small or young, they're not the target species, the fish have low commercial value, the catch exceeds the storage capacity of the vessel, the fish are damaged, etc. Precise estimates of global fish discards are difficult to obtain, but approximate

<footnote n="203">²⁰³Each fishery stock is weighted equally in this assessment. When the stocks are weighted by the volume of landings, the 62% figure increases to 77%.</footnote>

<footnote n="204">²⁰⁴These are the Atlantic (eastern central, northeast, northwest, southeast, southwest, western central), the Indian Ocean (eastern, western), the Mediterranean and Black Sea, and the Pacific (eastern central, northeast, northwest, southeast, southwest, western central).</footnote>
<figure><img src="image_255.png" /><figcaption>Figure 5.102: Estimated fish discards in Mt (1950–2018)</figcaption></figure>

Source: FishStat & www.ourworldindata.org/grapher/fish-discards.

values are available. Zeller et al. (2018) estimated that discards increased from 5 million tonnes per year in the early 1950s to a peak of 18.8 million tonnes in 1989, before declining to less than 10 million tonnes per year in recent years. This represented 10–20% of the total fish catch until 2000 and now represents less than 10% of the total annual catch. Similarly, Pérez Roda et al. (2019) estimated that annual discards averaged 9.1 million tonnes between 2010 and 2014, representing 10.8% of the total annual catch during this period. From a regional perspective, the northwest Pacific and northeast Atlantic together accounted for 39% of global discards. Among fisheries, those targeting crustaceans had the highest discard rates. In fact, the problem is not just bycatch, but fish waste in general. For example, Coppola et al. (2021) report that about two thirds of the total amount of fish is discarded. This explains why fish and seafood products provide about 1% of the total calories in the human diet at the global level. However, fish remains an important source of essential nutrients, providing omega-3 fatty acids, vitamins (A, B12 and D) and minerals such as iron (Fe), iodine (I), zinc (Zn) and calcium (Ca), which are essential for human health. Moreover, many local communities rely heavily on fisheries for their livelihoods. In this global context, the call of Worm et al. (2009) to rebuild global fisheries remains highly relevant (Duarte et al., 2020).

**Remark 67** To go further, the most prominent fisheries databases<sup>205</sup> include the FAO FishStat database, now called FishStatJ (data on fish production, trade and consumption), the RAM Legacy Stock Assessment database (a global compilation of detailed stock assessment data), and Sea Around Us (a research initiative that provides global fisheries catch reconstructions, including estimates of illegal, unreported and unregulated fishing).

<footnote n="205"><sup>205</sup>The websites are www.fao.org/fishery/en/statistics/software/fishstatj, www.ramlegacy.org and www.seaaroundus.org.</footnote>
**Overexploitation in tropical forests** By definition, overexploitation in tropical forest ecosystems is related to deforestation and habitat degradation. However, we need to distinguish between the two concepts: deforestation and overexploitation (Wilkie et al., 2011). According to Peres (2010), overexploitation of tropical forests involves three main issues:

* Timber extraction refers to the process of harvesting trees for commercial purposes, such as logging for wood, paper, and construction materials;

* Tropical forest vertebrates have been hunting in tropical forests for over 100 000 years, but their consumption increased during the 20th century;

* Non-timber forest products are biological resources such as plants and raw materials.

Rice et al. (1997) questioned the feasibility and effectiveness of sustainable forest management in tropical regions. They argued that sustainable logging in tropical forests is often ineffective because it yields less timber than conventional logging. Empirical studies support this (Pearce et al., 2003). Another important challenge is the lack of financial incentives for loggers to harvest at sustainable levels and invest in forest regeneration, as economic principles suggest that trees should be harvested when their volume growth rate falls below the prevailing interest rate (Peres, 2010). Delaying harvesting beyond this point entails an opportunity cost, as profits from immediate harvesting could be reinvested elsewhere for higher returns. Reynolds and Peres (2006) used a study of Bolivian mahogany by Raymond Gullison to illustrate this problem. Despite legal restrictions, trees as small as 40 cm in diameter were harvested — well below the legal limit — because at this size, mahogany trees grow in volume at a rate of 4% per year, and their market value increases at about 1% per year due to rising timber prices, while Bolivia's real interest rates averaged 17% in the mid-1990s. This significant gap between tree growth rates and high interest rates creates strong economic pressure to harvest trees as soon as they have market value, rather than waiting for them to mature.

Let us formalize the opportunity cost problem. If we denote by $\Delta p$ and $\Delta v$ the annual changes in timber prices and tree volume relative to a reference age $t_0$, the market value $W(t)$ of the trees is given by:

$$W(t) = p(t)v(t) = p_0v_0(1 + \Delta p)^{t-t_0}(1 + \Delta v)^{t-t_0}$$

where $p_0$ and $v_0$ are the price level and the volume of trees at age $t_0$. Now assume that trees are harvested at age $\tau \le t$ and the proceeds are invested at the risk-free rate $r$. The resulting wealth conditional on this harvest is equal to:

$$W(t | \tau \le t) = p(\tau)v(\tau)(1+r)^{t-\tau}$$

The economic objective is to maximize the conditional wealth $W(t | \tau \le t)$ or to find the optimal harvest age $\tau$ that maximizes the return. Figure 5.103 illustrates the economic problem with the following assumptions: $t_0 = 20$ years, $p_0 = \$500/m^3$, $v_0 = 2 m^3$, $\Delta p = 1\%$ and $\Delta v = 4\%$. If the tree is harvested at age 20, the income is $W(20) = 500 \times 2 = \$1000$. If the harvest is delayed by 30 years, the income increases to $W(50) = (500 \times 1.01^{30}) \times (2 \times 1.04^{30}) = \$4371.6$. Now suppose the interest rate is 3%, the income from logging at age 20 and reinvesting would be $W(50 | \tau = 20) = 1000 \times 1.03^{30} = \$2427.3$. Since $W(50 | \tau = 20) < W(50)$, there is a financial gain from waiting another 30 years before harvesting. However, if the interest rate is 7%, we have $W(50 | \tau = 20) =$
<figure><img src="image_256.png" /><figcaption>Figure 5.103: Opportunity cost of logging in tropical forests</figcaption></figure>

$1000 \times 1.07^{30} = \$7612.3$. This implies a significant opportunity cost for delaying the harvest$^{206}$. In general, there is an opportunity cost when the interest rate is relatively high, especially when $r \ge \Delta p + \Delta v$. According to Rice et al. (1997), there is no economic solution to this problem, and they suggest that protected areas are the only viable way to manage tropical forests sustainably. Twenty-five years later, the debate about selective logging and its impact on biodiversity remains open (Bicknell et al., 2015; Burivalova et al., 2021).

Hunting wild animals is a practice with deep historical roots, initially driven by the basic need for food. Today, food security in developed countries rarely depends on hunting. Conversely, it remains a vital source of food in many developing countries. In addition to providing food for personal consumption, hunting can be an important source of income for hunters and their families. In these cases, harvested animals are sold not only for food but also for other purposes, such as the production of leather goods and medicinal products. There is much evidence of overexploitation over the last fifty years, especially as the trade of wild animals has increased. This has two major consequences. First, hunting of wild animals causes biodiversity loss. For example, Peres and Palacios (2007) provided a meta-analysis of changes in population density for 30 species of mammals, birds, and reptiles in 101 forest sites. Populations declined by up to 75% in more intensively hunted areas compared to less intensively hunted areas. Of the 30 species studied, 22 declined significantly at high levels of hunting. As expected, body size significantly influenced the magnitude of changes

$$ \mathcal{C} = \underbrace{W(50 | \tau = 20)}_{\text{Income from 1st harvest}} + \underbrace{W(30 | \tau = 20)}_{\text{Income from 2nd harvest}} + \underbrace{W(10)}_{\text{3rd tree at age 10}} - \underbrace{W(50)}_{\text{Tree at age 50}} $$

<footnote>$^{206}$This opportunity cost is underestimated because two harvests could occur within 50 years. Therefore, the opportunity cost is given by:</footnote>
Box 5.26: The bushmeat crisis

Bushmeat is the meat of wild animals that are hunted for food (Nasi et al., 2008; Fa et al., 2002). The meat is either eaten by the hunter or sold to make money. In the media, the term bushmeat is generally used to refer to the illegal hunting of protected animals in Africa. This includes various species such as antelopes, monkeys, rodents and other wild animals. Bushmeat has historically been a vital protein source in parts of Africa, Latin America and South Asia. In remote rural areas of West and Central Africa, it constitutes 80–90% of animal protein intake. While subsistence hunting by local communities isn’t the main conservation issue, growing commercial demand is problematic. The market for bushmeat is now increasingly driven by urban consumers and diaspora communities, leading to unsustainable harvesting in several African regions.

Estimating the global impact of bushmeat harvesting is challenging. However, according to Nasi et al. (2011), “the harvest of animals such as tapir, duikers, deer, pigs, peccaries, primates and larger rodents, birds and reptiles [...] represents around 6 million tonnes of animals extracted yearly [...] with an estimated yearly extraction rate in the Congo Basin of 4.5 million tonnes.”. While more than 1 000 animal species are affected by bushmeat hunting, Ripple et al. (2016) estimated that approximately 300 of these terrestrial mammal species are threatened with extinction. This also means that the majority of mammal species (70%) are not listed as threatened on the IUCN Red List.

The term ‘bushmeat crisis’ refers to this paradox: the need for local people to hunt wild animals to improve their food security and well-being, while at the same time this practice has a significant negative impact on biodiversity. In this context, trade-offs and dilemmas are more difficult to resolve, as the study by Cawthorn and Hoffman (2015) shows.

in abundance, with large-bodied species declining faster in overhunted areas. Considering the 12 most hunted species, mean total biomass decreased almost elevenfold from 980 kg/km² in unhunted areas to only 89 kg/km² in highly hunted areas (Peres, 2010, page 111). The second consequence is the threat to the food security of local populations that depend on wildlife hunting. Indeed, hunting has become more sophisticated, systematic, and industrialized. For example, several studies indicate that African bushmeat has become an organized luxury market in African urban centers and restaurants (Gluszek et al., 2021), as well as in Europe (Gombeer et al., 2021), with porcupines, pangolins, antelopes, and snakes being the most sought-after products. For instance, Chaber et al. (2023) estimate that an average of 3.9 tonnes of bushmeat is smuggled through Brussels Airport each month. While the wildlife trade provides short-term financial benefits to hunters and their families, most do not make significant profits. Moreover, the ongoing loss of biodiversity today means food insecurity for these families in the future (Nasi et al., 2011).

Another way to understand the impact of overexploitation on biodiversity loss is the growth of trafficking in protected species of wild fauna and flora. According to Traffic (www.traffic.org), “the illegal trade in wild species is one of the most profitable criminal activities in the world, estimated to be worth up to $23 billion each year.” The UNODC (United Nations Office on Drugs and Crime) published the third edition of the World Wildlife Crime Report in 2024. This report shows that despite two decades of concerted action at the international and national levels and the entry into force in 1975 of CITES (the Convention on International Trade in Endangered Species of Wild Fauna and Flora), wildlife trafficking continues worldwide. Moreover, the report estimates that “wildlife crime is interconnected with the activities of large and powerful organized crime groups operating
Box 5.27: Operation Thunder 2024

On 4 February 2025, INTERPOL announced that nearly 20 000 live animals, all endangered or protected species, were seized in a global operation against wildlife and forestry trafficking networks jointly coordinated by INTERPOL and the World Customs Organization (WCO). Operation Thunder 2024 took place in 138 countries between 11 November and 6 December 2024. Authorities arrested 365 suspects and identified six transnational criminal networks suspected of trafficking in animals and plants protected by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). In addition to live animals, participating countries seized hundreds of thousands of protected animal parts and derivatives, trees, plants, marine life and arthropods. Timber cases represented the most significant seizures, occurring primarily in maritime container shipments, while most other seizures took place at airports and postal hubs. More than 100 companies involved in the trade of protected species were also identified. Significant seizures included:

* 134 tonnes of timber headed to Asia via ocean freight (Indonesia);

* 41 tonnes of exotic timber headed to Asia via ocean freight (Kenya);

* 4 472 kg of pangolin scales (Nigeria);

* 6 500 live songbirds discovered during a vehicle inspection at the Syrian border (Turkey);

* 5 193 live red-eared slider turtles concealed in passenger suitcases arriving from Malaysia at Chennai Airport (India);

* 3 700 protected plants intercepted en route from Ecuador (Peru);

* 8 rhino horns found in a suspect's luggage while transiting from Mozambique to Thailand (Qatar);

* One tonne of sea cucumbers, considered a seafood delicacy, smuggled from Nicaragua (United States);

* 973 kg of dried shark fins originating from Morocco seized at the airport (Hong Kong);

* 8 tigers, aged between two months and two years, discovered in a suspected illegal breeding facility (Czech Republic);

* 846 pieces of reticulated python skin, from the world's longest snake species, concealed onboard a ship (Indonesia).

Source: INTERPOL (2025), https://www.interpol.int/News-and-Events.
in some of the most fragile and diverse ecosystems from the Amazon to the Golden Triangle<fnref n="207" />.”
UNDOC (2024, page 46) reports that from 2015 to 2021, more than 140 000 seizures of wildlife
products were made in 162 countries, involving 4 000 different species. Analysis of seizure records
shows that coral pieces were the most common item found in the illegal wildlife trade, accounting
for 16% of the total number of seizures. Other seizures included crocodiles (9%), elephants (6%),
bivalves and carnivores (5% each), parrots and cockatoos (4%), orchids (4%), and many other
species. Figure 5.104 illustrates the most affected species based on the standardized seizure index,
which serves as a proxy for the market value of the seized goods. In this case, seizures of rhinos
(29%) rank first, followed by pangolins (28%) and elephants (15%).

<figure><img src="image_257.png" /><figcaption>Figure 5.104: Percentage share by species group aggregated by standardized seizure index (2015–2021)</figcaption></figure>

Source: UNDOC (2024, Figure 2.3, page 63).

The case of the rhinoceros is emblematic, as hunting has had a devastating impact on rhinoceros
populations, pushing several species to the brink of extinction since 1900. The number of black
rhinos declined by over 95% from around 100 000 in 1960 to fewer than 2 500 in the 1990s due to
hunting and poaching. Although conservation efforts have helped, they remain critically endangered
with only about 6 200 animals recorded in 2021. White rhinos were nearly extinct, with the southern
population falling to fewer than 100 individuals in the early 20th century. They have been saved by
rigorous conservation and breeding programs. As of 2021, there are approximately 16 000 individuals.
In contrast, the northern white rhino has virtually disappeared, with only two females remaining in
2021. Indian rhinos were reduced to less than 100 individuals in 1900 due to hunting, but have since

<footnote n="207">²⁰⁷The Golden Triangle refers to a mountainous region in Southeast Asia where the borders of Thailand, Laos and Myanmar meet.</footnote>
recovered thanks to conservation efforts and now number around 4000. Javan and Sumatran rhinos were already rare in 1900, but continued to decline due to hunting and habitat loss, and both species now number fewer than 100 individuals. In Figure 5.105, we show the evolution of the number of rhinos in the world. We observe that only three of the six species are really significant, and that the recovery since 1990 is mainly due to the expansion of the white rhino in southern Africa<fnref n="208" />.

<figure><img src="image_258.png" /><figcaption>Figure 5.105: Number of rhinoceros in the world (1960–2021)</figcaption></figure>

Source: www.ourworldindata.org/rhino-populations & Author's calculations.

Two decades ago, Bengis et al. (2004) and Kruse et al. (2004) raised concerns about the growing risk of zoonotic pandemics and the role of biodiversity loss, particularly deforestation and habitat alteration. Zoonoses are diseases transmissible from animals to humans caused by pathogens — viruses, bacteria, fungi, or parasites — that circulate naturally in animal populations<fnref n="209" />. In a landmark study, Taylor et al. (2001) analyzed 1415 human pathogenic species and found that 61% were zoonotic. Since then, the emergence of new diseases and pandemics, many of which are linked or suspected to be linked to the wildlife trade, has underscored these concerns. Examples include avian influenza (H5N1), COVID-19, Ebola, H1N1 influenza, MERS, SARS, and Zika. In addition, research has established or strongly suggested a zoonotic origin for diseases such as bubonic plague, chikungunya, dengue fever, HIV/AIDS, Lyme disease, the 1918 Spanish flu, salmonellosis, and rabies. It is also now widely accepted that hunting and the bushmeat trade have become important factors in the transmission of zoonotic diseases (Hilderink and De Winter, 2021). The case of SARS-CoV-2 (COVID-19) is emblematic. While many hypotheses were initially proposed, it is now widely accepted that bats and pangolins likely played a role as reservoirs or intermediate hosts in the transmission of the virus (Zhang et al., 2021). However, Bernstein et al. (2022) identified three key

<footnote n="208">²⁰⁸As of 2021, the numbers of rhinoceros are as follows: 15 940 southern white rhinos, 2 northern white rhinos, 6 195 black rhinos, 4 014 Indian rhinos, 76 Javan rhinos, and 41 Sumatran rhinos.</footnote>

<footnote n="209">²⁰⁹The list of major zoonotic diseases can be found in Rahman et al. (2020).</footnote>
areas for pandemic prevention: regulation of wildlife trade and hunting, mitigation of agricultural intensification and expansion, and conservation of tropical forests. The study also estimated that the cost of primary pandemic prevention measures is significantly less than the economic and human losses caused each year by emerging viral zoonoses.

The overexploitation of tropical forests is not limited to timber and wild animals. According to Peres (2010), it also includes plant products such as fruits, nuts, oil seeds, latex, resins, gums, medicinal plants, spices, dyes, ornamental plants, and raw materials such as firewood, climbing palms, bamboo, and rattan. Palm oil is a prominent example, and wild orchids are another<sup>210</sup>.

**Remark 68** More generally, overexploitation can be a threat to many natural resources, including fossil fuels, metal ores, non-metallic minerals, limestone and sand (IPBES, 2019).

### Climate change

The case of climate change is examined in detail in Part 2 of this Handbook. For example, Chapter 8 explains the concept and economic implications of climate change, while Chapter 12 discusses the physical risk of climate change. Climate change and biodiversity are inextricably linked. A rise in temperature, more intense precipitation, and an increase in natural disasters will naturally affect biodiversity. Animals such as butterflies, insects and birds are typical examples. Similarly, climate change has significant impacts on many aspects of non-animal biodiversity, including agriculture, forests, freshwater ecosystems and soil health.

### 5.4.4 Biodiversity measurement

Measuring biodiversity is essential for governments, regions, municipalities, companies, financial institutions and investors for two primary reasons. First, they operate within regulatory frameworks that increasingly require biodiversity risk monitoring<sup>211</sup>. Second, they must make decisions that either affect or are affected by biodiversity, a concept known as double materiality. For example, a company's corporate social responsibility strategy must include a biodiversity dimension, project financing should consider the potential for biodiversity loss, and governments need biodiversity metrics to develop effective conservation strategies and policies. Similar to ESG and climate risk assessment, measuring biodiversity risk requires the collection of relevant data. This data is then used within standardized methodologies to calculate biodiversity metrics, such as mean species abundance. In addition, a variety of commercial and open source solutions are available to assess biodiversity risk at various scales, including geospatial points, regional, national, and company-specific levels.

#### Essential biodiversity variables

Measuring biodiversity is complex due to its multifaceted nature and numerous dimensions. Moreover, even when focusing on a single dimension, data availability is often limited. However, these data are critical for assessing progress towards biodiversity goals. Mace and Baillie (2007) emphasized the importance of developing effective biodiversity indicators that are relevant to policy objectives and simple enough to facilitate comparisons between regions and countries. They discussed the distinction between pressures, status and responses, and called for urgent action to define a set of biodiversity indicators that are truly relevant for measuring biodiversity risks. Nearly twenty years

<footnote n="210"><sup>210</sup>According to UNODC (2024), the five most trafficked plant species are cedar and other sapindales, rosewood, agarwood and other myrtales, golden chicken fern, and orchids. Palm oil is not listed in CITES.</footnote>

<footnote n="211"><sup>211</sup>This is discussed further in the following section on biodiversity governance and regulation.</footnote>
later, significant progress has been made, but biodiversity measurement remains a challenge due to the lack of consistent and clear indicators. The article by Mace and Baillie was written in the context of the 2010 Biodiversity Target adopted by the Convention on Biological Diversity (CBD), whose objective was to “halt the loss of biological diversity at all levels by the year 2010.” The monitoring of progress was defined with respect to 22 headline indicators<fnref n="212" />. In fact, a number of these indicators were vague, for example the indicators (8) Ecological footprint and related concepts, (10) Trends in invasive alien species and (15) Incidence of human-induced ecosystem failure.

<table><caption>Table 5.66: EBV classes and names</caption><thead><tr><td>#</td><td>EBV class</td><td>EBV theme</td></tr></thead><tbody><tr><td>1</td><td>Genetic composition</td><td>Genetic diversity (richness and heterozygosity), genetic differentiation (number of genetic units and genetic distance), effective population size, inbreeding</td></tr><tr><td>2</td><td>Species populations</td><td>Species distributions, species abundances</td></tr><tr><td>3</td><td>Species traits</td><td>Morphology, physiology, phenology, movement, reproduction</td></tr><tr><td>4</td><td>Community composition</td><td>Community abundance, taxonomic/phylogenetic diversity, trait diversity, interaction diversity</td></tr><tr><td>5</td><td>Ecosystem functioning</td><td>Primary productivity, ecosystem phenology, ecosystem disturbances</td></tr><tr><td>6</td><td>Ecosystem structure</td><td>Live cover fraction, ecosystem distribution, ecosystem vertical profile</td></tr></tbody></table>

Source: https://geobon.org/ebvs/what-are-ebvs.

The lack of clear indicators led Pereira et al. (2013) to introduce the concept of essential biodiversity variables (EBVs), with the aim of establishing a standardized framework for monitoring biodiversity change worldwide:

> “Despite progress in digital mobilization of biodiversity records and data standards, there is insufficient consistent national or regional biodiversity monitoring and sharing of such information. Along with inadequate human and financial resources, a key obstacle is the lack of consensus about what to monitor. Many initiatives collect data that could be integrated into an EBV global observation network, though important gaps remain. Different organizations and projects adopt diverse measurements, with some important biodiversity dimensions, such as genetic diversity, often missing.” (Pereira et al., 2013, page 277).

The essential biodiversity variables are maintained by the Group on Earth Observations Biodiversity Observation Network<fnref n="213" /> (GEO BON). Table 5.66 shows the 6 EBV classes and the associated EBV themes<fnref n="214" />. Schmeller et al. (2018) proposed to focus on the eight candidate EBVs given in Table 5.67. Many other indicators have been proposed by the scientific community, the latest and most promising indicators are certainly the remote sensing geospatial patterns measured by satellites (Skidmore et al., 2021). All these indicators can be used to build a biodiversity scoring system. However, the lack of consensus and standardization remains an obstacle to biodiversity monitoring.

<footnote n="212">²¹²For instance, the first three indicators were (1) Trends in extent of selected biomes, ecosystems, and habitats, (2) Trends in abundance and distribution of selected species and (3) Coverage of protected areas.</footnote>

<footnote n="213">²¹³The website is www.geobon.org, while the EBV datasets are available at https://portal.geobon.org/datasets.</footnote>

<footnote n="214">²¹⁴Here are some examples of EBV indicators promoted by GEO-BON: Biodiversity Habitat Index (BHI), Genetic Diversity Indicator (GDI), Global Ecosystem Restoration Index (GERI), Local Biodiversity Intactness Index (LBII),</footnote>
<table><caption>Table 5.67: Eight essential biodiversity variables (Schmeller et al., 2018)</caption><thead><tr><td>Indicator</td><td>Definition</td></tr></thead><tbody><tr><td>Abundance</td><td>Abundance is the number of individuals of a species within a local population.</td></tr><tr><td>Allelic diversity</td><td>Allelic diversity is the average number of alleles per locus in a population of a given species.</td></tr><tr><td>Body mass</td><td>Body mass scaled by body size, or the body mass index (BMI), indicates the condition and energy reserves of animals.</td></tr><tr><td>Ecosystem heterogeneity</td><td>Ecosystem heterogeneity describes the amount of variability in space and time of ecosystems.</td></tr><tr><td>Phenology</td><td>Phenology is defined as annually recurring life-cycle events, such as the timing of migration or flowering.</td></tr><tr><td>Range dynamics</td><td>Range dynamics are changes in species distributions through time, space and shape. This EBV is derived from the species distribution EBV for detecting critical ecological change early.</td></tr><tr><td>Size at first reproduction</td><td>Size at first reproduction is the individual body size (length) reached by an organism at the time when its first reproduction occurs.</td></tr><tr><td>Survival rates</td><td>Survival rate is the average probability that an organism will stay alive between two time points.</td></tr></tbody></table>

Source: Schmeller et al. (2018).

## Biodiversity metrics

We have already mentioned the Living Planet Index and the Red List Index<fnref n="215" />. These indices focus on the extinction risk of species, and the better geographic resolution we have is the country. Below we present alternative simple measures of biodiversity that are available at higher resolutions.

**Mean species abundance (MSA)** Mean species abundance is one of the most popular biodiversity indicators because it is easy to understand and has been widely popularized by GLOBIO (www.globio.info). Let $n_i$ be the abundance of species $i$ in an area $A$, $n_i^*$ be the abundance of species $i$ in a reference state, and $S_A$ be the number of native species in the area. The MSA of area $A$ is calculated as follows:

$$MSA = \frac{1}{S_A} \sum_{i=1}^{S_A} \min \left( \frac{n_i}{n_i^*}, 1 \right)$$

By construction we have $MSA \in [0, 1]$. An MSA of 1 corresponds to an undisturbed area, while a low MSA value indicates a highly disturbed area, where many native species have disappeared or experienced significant population declines. Consider the example illustrated in Figure 5.106. There are four native species in the reference area. In the disturbed area, the parrots have disappeared and have been replaced by rodents. The MSA is then calculated as follows:

$$MSA = \frac{1}{4} \left( \frac{0}{2} + \frac{2}{4} + \frac{3}{4} + \frac{1}{2} \right) = 43.75\%$$

<footnote>Protected Area Representativeness & Connectedness indices (PARC), Invasive Alien Species Rate (IAS), Species Habitat Index (SHI), Species Protection Index (SPI), and Species Status Information Index (SSII).</footnote>

<footnote n="215">²¹⁵See Chapter 2 on pages 62–64.</footnote>
<figure><img src="image_259.png" /><figcaption>Figure 5.106: Computation of the MSA</figcaption></figure>

In GLOBIO, the MSA is calculated for different pressures: land use, climate change, roads, nitrogen deposition, hunting. An overall MSA is calculated by combining the MSA of the different pressures (Alkemade et al., 2009):

$$MSA = \prod_{j=1}^{p} MSA_{(j)}$$

where $MSA_{(j)}$ is the MSA for pressure $j$ and $p$ is the number of pressures (between 1 and 5). According to Schipper et al. (2020), the contribution of pressure $j$ to biodiversity loss is equal to:

$$C_{(j)} = \frac{(1 - MSA_{(j)})}{\sum_{j=1}^{p} (1 - MSA_{(j)})} (1 - MSA)$$

where $1 - MSA_{(j)}$ is the biodiversity loss for pressure $j$.

Figure 5.107 shows global MSA values for the year 2015. Notably, MSA values approach one in polar regions and deserts. This pattern requires careful interpretation because the MSA does not measure biodiversity richness, but rather the intactness of biodiversity relative to an undisturbed reference state (Schipper et al., 2020). In naturally species-poor ecosystems such as deserts, tundra, and polar regions, where reference biodiversity is already low, even limited human disturbance results in high MSA values. This reflects minimal deviation from the natural state rather than high biodiversity. In essence, when the reference biodiversity of a region is naturally low, the potential for biodiversity loss is limited, resulting in MSA values close to one in these ecosystems despite their relatively low species richness. This illustrates an important characteristic of the MSA metric: it quantifies the relative preservation of native ecological communities rather than absolute biodiversity.

**Remark 69** Since the release of the first version of GLOBIO in 2000, the model has been improved and enriched over the years. Three extensions of GLOBIO have been developed to cover additional relevant aspects of nature. GLOBIO-ES models changes in global ecosystem services by assessing current conditions, trends and future scenarios of nature's benefits to humans, such as food, water, climate regulation, soil health and health support. GLOBIO-Aquatic models the health of freshwater ecosystems by quantifying biodiversity (MSA) and water quality (algal blooms) based on human pressures such as land use, flow alteration, eutrophication and temperature. GLOBIO-Species models how human pressures affect the distribution and population size of individual vertebrate species, enabling the calculation of biodiversity indicators such as the RLI and LPI metrics to track progress towards biodiversity goals.
<figure><img src="image_260.png" /><figcaption>Figure 5.107: Mean species abundance values for 2015 (GLOBIO 4)</figcaption></figure>

Source: Schipper et al. (2020, Figure 4(a), page 766).

**Potentially disappeared fraction (PDF)** The potentially disappeared fraction is a metric used to assess the biodiversity loss due to environmental change, particularly human activities such as pollution, habitat destruction, and climate change. Originally developed by Müller-Wenk (1998), it has been widely used in life cycle assessment (LCA) models to evaluate the environmental footprint of products and activities. PDF represents the fraction of species that have disappeared or are expected to disappear from a region due to environmental pressures such as land use, climate change, or pollution<fnref n="216" />. The PDF of area A is:

$$PDF = \frac{S_0 - S_A}{S_0} = \frac{1}{S_0} \sum_{j=1}^{S_0} 1\{j \notin A\}$$

where $S_0$ is the undisturbed species richness of A, $S_A$ is the current species richness of A, and j is the species index. PDF equals zero if no species disappear (no biodiversity loss), while PDF equals one if all species in the considered ecosystem disappear (total biodiversity loss). PDF is equal to 25% for the area shown in Figure 5.106, because 25% of the species in this area have disappeared (parrot species have disappeared, while frogs, trees, and owls remain).

The PDF approach has been popularized by the ReCIPe LCA model (Goedkoop et al., 2008), which provides characterization factors (CFs) that translate human interventions in the environment (emissions, resource use, land use) into potential impacts on biodiversity, often expressed as PDF values. More complex approaches have been developed to calculate PDFs and CFs, such as the model of Kuipers et al. (2021), which uses the species-area relationship and defines new characterization factors<fnref n="217" />. The unit PDF.m².yr is often used. It represents the potential area (in square meters) where all species are potentially lost per year. For instance, 10 PDF.m².yr means that 10 m² has lost all its species during a year.

<footnote n="216">²¹⁶We have already encountered the PDF measure when studying the species-area relationship. The PDF measure is a generalization of the metric *Loss*<sub>species</sub> when the pressures are not limited to habitat loss (see Equation (5.19) on page 435).</footnote>

<footnote n="217">²¹⁷CF and PDF values can be found in the Supplementary Data available online (Tables S2 and S3).</footnote>
**Biodiversity intactness index (BII)** A biodiversity intactness index is a metric that aims to measure how much of a region's natural biodiversity remains, despite human impacts. For instance, if we measure intactness at the species level, we can define the BII from the PDF:

$$ \text{BII} = 1 - \text{PDF} $$

Scholes et al. (2005) proposed the following empirical estimator of the biodiversity intactness index:

$$ \text{BII} = \frac{\sum_{i} \sum_{j} \sum_{k} S_{i,j} A_{j,k} I_{i,j,k}}{\sum_{i} \sum_{j} \sum_{k} R_{i,j} A_{j,k}} \quad (5.40) $$

where *i* is the taxon index, *j* is the ecosystem index, *k* is the land use index, *S*<sub>*i*,j*</sub> is the species richness of taxon *i* in ecosystem *j*, *A*<sub>*j*,k*</sub> is the area of land use *k* in ecosystem *j*, and *I*<sub>*i*,j,k*</sub> is the population impact or relative population of taxon *i* (compared to the reference state) under land use *k* in ecosystem *j*. We generally assume that *I*<sub>*i*,j,k*</sub> ≤ 1, but there may be special situations where the population has increased, meaning that *I*<sub>*i*,j,k*</sub> may be greater than 1. At first glance, Formula (5.40) seems complex, but it is simply a weighted average of the various population impacts:

$$ \text{BII} = \sum_{i} \sum_{j} \sum_{k} w_{i,j,k} I_{i,j,k} $$

where $w_{i,j,k} = \frac{S_{i,j} A_{j,k}}{\sum_{i} \sum_{j} \sum_{k} R_{i,j} A_{j,k}}$ and the sum of weights is equal to one — $\sum_{i} \sum_{j} \sum_{k} w_{i,j,k} = 100\%$. If there is only one ecosystem and one land use, Formula (5.40) reduces to the weighted average of the population impacts where the weights are proportional to the species richness *S*<sub>*i*</sub> of taxon *i*. For example, assuming there are three taxonomic groups (birds, mammals, and plants), the species richness is 100 bird species, 50 mammal species, 200 plant species, and the population impacts are 50%, 80%, and 90%, respectively, we get:

$$ \text{BII} = \frac{100 \times 50\% + 50 \times 80\% + 200 \times 90\%}{100 + 50 + 200} = \frac{270}{350} = 77.14\% $$

<table><caption>Table 5.68: Biodiversity intactness index in % of tropical forests (2001–2012)</caption><thead><tr><th rowspan="2">Region</th><th rowspan="2">Metric</th><th colspan="8">ISO code</th></tr><tr><th>ARG</th><th>BOL</th><th>BRA</th><th>CHL</th><th>COL</th><th>CUB</th><th>PER</th><th>PRY</th></tr></thead><tbody><tr><td rowspan="3">South America</td><td>2001 BII</td><td>48.3</td><td>72.8</td><td>82.7</td><td>14.6</td><td>81.2</td><td>18.0</td><td>88.2</td><td>58.2</td></tr><tr><td>2012 BII</td><td>46.4</td><td>71.2</td><td>80.7</td><td>16.1</td><td>80.0</td><td>19.3</td><td>87.5</td><td>53.0</td></tr><tr><td>Change (in %)</td><td>-3.8</td><td>-2.2</td><td>-2.4</td><td>10.2</td><td>-1.4</td><td>7.8</td><td>-0.8</td><td>-8.9</td></tr><tr><td rowspan="3">Africa</td><td>2001 BII</td><td>57.0</td><td>79.7</td><td>84.2</td><td>89.7</td><td>87.9</td><td>72.6</td><td>60.2</td><td>58.7</td></tr><tr><td>2012 BII</td><td>41.9</td><td>79.3</td><td>83.2</td><td>88.8</td><td>87.3</td><td>72.8</td><td>57.2</td><td>57.7</td></tr><tr><td>Change (in %)</td><td>-26.4</td><td>-0.5</td><td>-1.2</td><td>-1.1</td><td>-0.7</td><td>0.3</td><td>-4.9</td><td>-1.8</td></tr><tr><td rowspan="3">South Asia</td><td>2001 BII</td><td>38.6</td><td>41.2</td><td>75.8</td><td>13.3</td><td>64.5</td><td>79.6</td><td>31.0</td><td>39.5</td></tr><tr><td>2012 BII</td><td>36.4</td><td>34.5</td><td>70.4</td><td>13.0</td><td>61.3</td><td>70.5</td><td>29.7</td><td>38.2</td></tr><tr><td>Change (in %)</td><td>-5.5</td><td>-16.2</td><td>-7.1</td><td>-1.5</td><td>-4.9</td><td>-11.4</td><td>-4.2</td><td>-3.4</td></tr></tbody></table>

Source: De Palma et al. (2021), https://doi.org/10.5519/5wriutqz & Author's calculations.
The calculation of the biodiversity intactness index requires the collection of population impacts for different pressures and taxa. Data sets can be found on various websites such as www.nhm.ac.uk/our-science/services/data/biodiversity-intactness-index.html. In Table 5.68 we report the values of the biodiversity intactness index in tropical forests calculated by De Palma et al. (2021) between 2001 and 2012. We find high heterogeneity even within the same region. For example, Peru had a BII of 88% in 2012, while it was only 19% in Argentina. Côte d'Ivoire experienced the largest decline (−26%), while the intactness of biodiversity in Chile improved by 10% between 2011 and 2012.

**Species threat abatement and restoration (STAR)** The species threat abatement and restoration (STAR) metric is a global framework designed to quantify and guide efforts to reduce biodiversity loss. It measures the potential contribution of specific conservation actions (reducing pressure on species and restoring habitats) to improving the status of threatened species. According to Mair et al. (2021), for a given location *i* and a given threat *j*, the STAR threat-abatement score is calculated as a weighted average of the species IUCN Red List status:

$$T_{i,j} = \sum_{s=1}^{S} T_{i,j}^{(s)} = \sum_{s=1}^{S} \pi_{i,s} w_s c_{j,s}$$

where $\pi_{i,s} \in [0, 1]$ is the current area of habitat (AOH) of species *s* within location *i* — expressed as a percentage of the current global AOH of the species, $w_s \in \{1, 2, 3, 4\}$ is the IUCN Red List category weight<fnref n="218" /> of species *s*, $c_{j,s}$ is the relative contribution of threat *j* to the extinction risk of species *s*, and *S* is the species richness at location *i*. The STAR restoration score for a given location *i* and a given threat *j* is calculated as:

$$R_{i,j} = \sum_{s=1}^{S} R_{i,j}^{(s)} = \sum_{s=1}^{S} \varphi_{i,s} w_s c_{j,s} m_{i,s}$$

where $\varphi_{i,s} \in [0, 1]$ is the amount of restorable AOH for species *s* at location *i* — expressed as a percentage of the current global AOH of the species, and $m_{i,s} > 0$ is a multiplier appropriate for the habitat at location *i* to discount restoration results — the default value is 29%. The scores $T_{i,j}$ and $R_{i,j}$ can be decomposed to obtain the contribution $T_{i,j}^{(s)}$ and $R_{i,j}^{(s)}$ of each species. By construction, the contributions are between 0 and 1, while the scores are between 0 and the species richness *S*. Below, we provide an example to compute $T_{i,j}$ and $R_{i,j}$ and their species contribution $T_{i,j}^{(s)}$ and $R_{i,j}^{(s)}$:

<table><thead><tr><th>Species</th><th>Red List</th><th>w<sub>s</sub></th><th>π<sub>i,s</sub></th><th>c<sub>j,s</sub></th><th>φ<sub>i,s</sub></th><th>m<sub>i,s</sub></th><th>T<sub>i,j</sub><sup>(s)</sup></th><th>R<sub>i,j</sub><sup>(s)</sup></th></tr></thead><tbody><tr><td>Salmo salar (salmon)</td><td>NT</td><td>1</td><td>25%</td><td>90%</td><td>10%</td><td>29%</td><td>0.225</td><td>0.026</td></tr><tr><td>Phengaris teleius (butterfly)</td><td>VU</td><td>2</td><td>50%</td><td>90%</td><td>25%</td><td>29%</td><td>0.900</td><td>0.131</td></tr><tr><td>Conraua goliath (frog)</td><td>EN</td><td>3</td><td>80%</td><td>80%</td><td>25%</td><td>29%</td><td>1.920</td><td>0.174</td></tr><tr><td>Pericallis malvifolia (magnolia)</td><td>CR</td><td>4</td><td>75%</td><td>80%</td><td>20%</td><td>29%</td><td>2.400</td><td>0.186</td></tr><tr><td>Total</td><td></td><td></td><td></td><td></td><td></td><td></td><td>5.445</td><td>0.516</td></tr></tbody></table>

The site contains four species, each belonging to a different IUCN Red List category. Salmon occupy 25% of the habitat, indicating this is either a marine site or one with rivers. The threat contribution is high at 90%, meaning this threat is responsible for 90% of the extinction risk to salmon. Potential

<footnote n="218">²¹⁸ *w*<sub>s</sub> takes the values 1, 2, 3, and 4 for near threatened, vulnerable, endangered, and critically endangered, respectively.</footnote>
habitat restoration is 10%, suggesting we can reduce extinction risk by that amount. This yields an absolute contribution of 0.225 for salmon, representing 4.1% of the total threat-abatement score. In contrast, magnolias represent 44% of the threat-abatement score due to two main factors: they cover a larger habitat area, and the species *Pericallis malvifolia* is classified as critically endangered on the IUCN Red List.

Figure 5.108: Global STAR threat-abatement score for amphibians, birds and mammals (at a 50-km grid cell resolution)

<figure><img src="image_261.png" /></figure>

Source: Mair et al. (2021, Figure 2).

Figure 5.108 illustrates the global STAR threat-abatement scores for amphibians, birds, and mammals as calculated by Mair et al. (2021). The color gradient ranges from yellow (low scores) to green (high scores). The distribution shows that biodiversity conservation priorities are geographically concentrated in some regions, particularly South America, South Asia, and southern Africa, suggesting that effective biodiversity risk management requires targeted approaches in these hotspots:

> "While every nation can contribute towards halting biodiversity loss, Indonesia, Colombia, Mexico, Madagascar and Brazil combined have stewardship over 31% of total STAR values for terrestrial amphibians, birds and mammals. Among actions, sustainable crop production and forestry dominate, contributing 41% of total STAR values for these taxonomic groups. Key Biodiversity Areas cover 9% of the terrestrial surface but capture 47% of STAR values." (Mair et al., 2021, page 836).

**Comparison of these methodologies** Which methodology is best? There is no definitive answer. First, in addition to the widely accepted approaches, there are numerous other valuable methodologies that receive less attention but provide important insights into biodiversity assessment. Second, these methodologies target different aspects of biodiversity — from species abundance and richness to density and ecosystem integrity — making direct comparisons problematic. Third, while all of these methodologies require substantial data inputs, they often present simplified perspectives by focusing on single dimensions of biodiversity. In particular, they focus primarily on species popula-
tions, which represent only one of the six essential biodiversity variables. This explains why these methods are so closely related (Rossberg, 2022; Rossberg et al., 2023). Fourth, a major limitation of these approaches is their general failure to incorporate ecosystem services — a critical dimension for a comprehensive understanding of biodiversity and its relationship to human well-being.

Commercial solutions

In addition to the established biodiversity measurement practices seen previously, a wide range of commercial approaches has emerged, offering diverse tools such as datasets, analytical software, calculation methods and comprehensive assessment services. In their Update Report 5 for the EU Business & Biodiversity Platform, De Ryck et al. (2024) documented 37 different approaches, indicating a significant increase in demand for biodiversity advisory services. However, concerns remain about the robustness and long-term viability of these tools. This pattern mirrors the evolution of ESG measurement, which has experienced rapid expansion followed by a period of consolidation. Critically, despite widespread agreement on the need for standardization and alignment, neither regulatory nor voluntary disclosure frameworks mandate specific measurement approaches. This is a significant barrier.

Table 5.69 provides an overview of available biodiversity assessment solutions. De Ryck et al. (2024) proposes a framework for evaluating these tools based on eight key criteria: business context, biodiversity pressures, level of ambition, scope, metrics, data requirements, implementation effort, and sector applicability. This framework allows companies to select methodologies that meet their specific needs and capabilities<fnref n="219" />. The landscape of biodiversity assessment tools varies widely in specialization — some are tailored to specific industries such as finance, mining or agriculture, while others are broadly applicable. These solutions also vary in their measurement granularity, with capabilities ranging from localized assessments (site or project level) to broader assessments (product, company or entire supply chain analysis). They also address different dimensions of biodiversity, including species diversity, habitat integrity, and ecosystem services, while accounting for different environmental pressures, such as land-use change, climate impacts, pollution sources, and the spread of invasive species. A critical criterion for selecting an approach is the scope of the solution, which defines the boundaries of what is included when measuring impacts and dependencies. These scopes can be categorized as follows<fnref n="220" />:

1. Scope 1: Impacts generated within the entity's control and other impacts directly caused by the entity during the assessment period;

2. Scope 2: Impacts resulting from the generation of non-fuel energy (electricity, steam, heat and cooling) for use at the site level, including impacts from land use change, fragmentation and related factors;

3. Scope 3

(a) Scope 3 Upstream: Impacts that are a consequence of the company's activities, but are caused by sources not owned or controlled by the company within its upstream supply chain;

(b) Scope 3 Downstream: Impacts that are a consequence of the company's activities, but are caused by sources not owned or controlled by the company within its downstream consumption and waste processes.

<footnote n="219">²¹⁹See also Bailon et al. (2024) for a comparison of the different solutions.</footnote>

<footnote n="220">²²⁰These scope definitions are based on the GHG Protocol and are analogous to the scope definitions used to measure GHG emissions (see Section 9.1.3 on page 878).</footnote>
<table><caption>Table 5.69: List of commercial solutions for measuring biodiversity</caption><thead><tr><th>Sigle</th><th>Name</th><th>Sponsors</th><th>OS‡</th></tr></thead><tbody><tr><td>ABD Index</td><td>AgroBioDiversity Index</td><td>Alliance of Bioversity International, CIAT</td><td></td></tr><tr><td>B-INTACT</td><td>Biodiversity Integrated Assessment Computation Tool</td><td>FAO</td><td>✓</td></tr><tr><td>BFFI</td><td>Biodiversity Footprint for Financial Institutions</td><td>ASN Bank, CREM, PRé Sustainability Plansup</td><td>✓</td></tr><tr><td>BFM</td><td>Biodiversity Footprint Methodology</td><td>CDC Biodiversité, Carbon4 Finance</td><td></td></tr><tr><td>BIA-GBS</td><td>Biodiversity Impact Analytics – Global Biodiversity Score</td><td>CDC Biodiversité, Carbon4 Finance</td><td></td></tr><tr><td>BIAT</td><td>Biodiversity Impact Assessment Tool</td><td>ISS ESG</td><td></td></tr><tr><td>BII</td><td>Biodiversity Intactness Index</td><td>Natural History Museum (UK)</td><td></td></tr><tr><td>BIM</td><td>Biodiversity Impact Metric</td><td>Cambridge Institute for Sustainable Leadership</td><td></td></tr><tr><td>BRF</td><td>Biodiversity Risk Filter</td><td>WWF</td><td>✓</td></tr><tr><td>CBF</td><td>Corporate Biodiversity Footprint</td><td>Iceberg Databab</td><td></td></tr><tr><td>ENCORE</td><td>Exploring Natural Capital Opportunities, Risks and Exposure</td><td>Global Canopy, UNEP FI, UNEP-WCMC</td><td>✓</td></tr><tr><td>GBS</td><td>Global Biodiversity Score</td><td>CDC Biodiversité</td><td></td></tr><tr><td>GBSFI</td><td>Global Biodiversity Score for Financial Institutions</td><td>CDC Biodiversité</td><td></td></tr><tr><td>GID</td><td>Global Impact Database</td><td>Impact Institute</td><td></td></tr><tr><td>GIST NBS</td><td>Nature &amp; Biodiversity Suite (BIGER/SLAM/DIRO 360)</td><td>GIST Impact</td><td></td></tr><tr><td>IBAT</td><td>Integrated Biodiversity Assessment Tool</td><td>BirdLife International, Conservation International, IUCN, UNEP-WCMC</td><td></td></tr><tr><td>InVEST</td><td>Integrated Valuation of Ecosystem Services and Trade-offs</td><td>Natural Capital Project</td><td>✓</td></tr><tr><td>MBFM</td><td>MSCI Biodiversity Footprint Metrics</td><td>MSCI</td><td></td></tr><tr><td>NRP</td><td>Nature Risk Profile</td><td>S&P Global</td><td></td></tr><tr><td>NVE</td><td>Nature Value Explorer</td><td>Flemish Institute for Technological Research</td><td>✓</td></tr><tr><td>PBF</td><td>Product Biodiversity Footprint</td><td>I Care</td><td></td></tr></tbody></table>

<footnote>‡OS stands for Open Source.</footnote>
Comparison of biodiversity assessment solutions reveals a paradoxical landscape characterized by both significant uniformity and heterogeneity. On the one hand, there is considerable homogeneity in the basic approaches, with most methodologies primarily emphasizing metrics of species abundance and diversity. Many solutions are based on identical underlying data sets, which are simply presented through different interfaces or analytical frameworks. On the other hand, there is considerable heterogeneity in the maturity of these solutions. Established tools have been widely adopted by many institutions over long periods of time and have evolved into comprehensive, integrated platforms. Meanwhile, other solutions remain in earlier stages of development, functioning essentially as proofs of concept or experimental approaches with limited implementation history.

### 5.4.5 Biodiversity governance and regulation

Biodiversity risk, like climate risk, is subject to regulation, and its governance has evolved significantly in recent years. While the political agenda may lack clarity, its mere existence represents progress. In particular, the Conference of the Parties has recently received more media attention than in previous years.

#### Convention on Biodiversity (CBD)

The Convention on Biological Diversity was adopted at the 1992 Earth Summit in Rio de Janeiro and entered into force in 1993. The purpose of this international treaty is to address the global loss of biological diversity, with the following objectives:

1. The conservation of biological diversity;

2. The sustainable use of its components;

3. The fair and equitable sharing of the benefits arising out of the utilization of genetic resources.

Similar to the United Nations Framework Convention on Climate Change (UNFCCC), the Conference of the Parties (COP) serves as the governing body of the CBD, meeting every two years to make key decisions. Some of the major treaties and initiatives adopted under the CBD include:

* The International Coral Reef Initiative (1994, COP1, Bahamas), a partnership of nations and organizations to protect coral reefs;

* The Cartagena Protocol on Biosafety (2000), which regulates the international movement of living modified organisms to ensure biosafety;

* The Nagoya Protocol on Access and Benefit-Sharing (2010, COP10, Japan), which establishes a legal framework for the equitable sharing of benefits arising from the use of genetic resources, and adopts the Aichi Biodiversity Targets (2011–2020), which set 20 global targets for biodiversity conservation;

* The Pyeongchang Roadmap (2014, COP12, South Korea), which aims to accelerate global efforts to achieve the Aichi Biodiversity Targets;

* The Kunming-Montreal Global Biodiversity Framework, known as the GBF (2022, COP15), which includes the goal of protecting 30% of the Earth's land and marine areas by 2030 (the 30 × 30 target).
<table><caption>Table 5.70: Aichi Biodiversity Targets (2011–2020)</caption><tr><td>Strategic Goal A</td><td>Address the underlying causes of biodiversity loss by mainstreaming bio-diversity across government and society (Target 1–4)</td></tr><tr><td>Strategic Goal B</td><td>Reduce the direct pressures on biodiversity and promote sustainable use (Target 5–10)</td></tr><tr><td>Strategic Goal C</td><td>To improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity (Target 11–13)</td></tr><tr><td>Strategic Goal D</td><td>Enhance the benefits to all from biodiversity and ecosystem services (Target 14–16)</td></tr><tr><td>Strategic Goal E</td><td>Enhance implementation through participatory planning, knowledge management and capacity building (Target 17–20)</td></tr><tr><td>Target 5</td><td>By 2020, the rate of loss of all natural habitats, including forests, is at least halved and, where feasible, brought close to zero, and degradation and fragmentation are significantly reduced</td></tr><tr><td>Target 7</td><td>By 2020 areas under agriculture, aquaculture and forestry are managed sustainably, ensuring conservation of biodiversity</td></tr><tr><td>Target 8</td><td>By 2020, pollution, including from excess nutrients, has been brought to levels that are not detrimental to ecosystem function and biodiversity</td></tr><tr><td>Target 9</td><td>By 2020, invasive alien species are identified, priority species are controlled or eradicated, and measures are in place to manage pathways to prevent their introduction and establishment</td></tr><tr><td>Target 11</td><td>By 2020, at least 17% of terrestrial and inland water areas and 10% of coastal and marine areas are protected by well-connected systems of protected areas</td></tr><tr><td>Target 12</td><td>By 2020, the extinction of known threatened species has been prevented, and their conservation status has been improved and maintained, especially for those species most in decline</td></tr><tr><td>Target 15</td><td>By 2020, the resilience of ecosystems has been enhanced, including restoration of at least 15% of degraded ecosystems</td></tr><tr><td>Target 20</td><td>By 2020, the goal is to significantly increase financial resources for effective implementation of the Strategic Plan for Biodiversity 2011–2020</td></tr></table>

Source: https://www.cbd.int/sp/targets.

**Aichi Biodiversity Targets** The Aichi targets are a set of 20 global biodiversity goals adopted at the 10th Conference of the Parties in Japan in 2010. These 20 targets are grouped into five strategic goals, as shown in Table 5.70. The overall objective is to reduce the rate of biodiversity loss, as reflected in some of the targets listed in Table 5.70. However, there is broad consensus that the world has failed to achieve any of the Aichi targets. Several factors have contributed to this failure. First, many of the targets are vague and lack clear, enforceable commitments, making it difficult to hold countries accountable. Enforcement mechanisms are limited, and the wording of many targets leaves room for interpretation. For example, Target 7 states that “by 2020 areas under agriculture, aquaculture and forestry are managed sustainably, ensuring conservation of biodiversity.” But what does that mean in practice? What specific actions should be taken? What metrics should be used to assess sustainability in these sectors? The lack of clear definitions and measurable indicators has weakened the impact of the targets. The second factor is inadequate funding, which creates a significant gap between what is needed and what is available for biodiversity conservation projects.
For example, Target 20 states that “by 2020, at the latest, the mobilization of financial resources for effectively implementing the Strategic Plan for Biodiversity 2011–2020 from all sources, and in accordance with the consolidated and agreed process in the Strategy for Resource Mobilization, should increase substantially from the current levels.” McCarthy et al. (2012) examined the financial costs of Targets 11 and 12, which relate to protected areas and extinction prevention. For Target 11, they estimated that protecting and effectively managing all terrestrial areas of global importance for bird conservation would cost $65.1 billion annually, and adding areas for other taxa would increase this to $76.1 billion annually. For Target 12, they estimated that reducing the risk of extinction of all globally threatened bird species by at least one IUCN Red List category would cost between $875 million and $1.23 billion, representing only 12% of current funding. In another study, by comparing actual expenditures with expected levels, Waldron et al. (2013) identified 40 severely underfunded countries, with the top five being Iraq, Djibouti, Angola, Kyrgyzstan, and Guyana. Most of the countries in this ranking are developing countries, with the exception of five developed countries: Finland, Iceland, France, Australia and Austria. More recently, the Paulson Institute, the Nature Conservancy, and the Cornell Atkinson Center for Sustainability conducted a comprehensive review of global biodiversity finance and concluded that there is a huge funding gap:

> “This report determines that, in 2019, the total global annual flow of funds toward biodiversity protection amounted to approximately $124–143 billion per year against an estimated annual need of $722–967 billion to halt the decline in global biodiversity between now and 2030. Taken together, these figures reveal a biodiversity financing gap of $598–824 billion per year. [...] Significantly, this report shows that annual governmental expenditures on activities harmful to biodiversity in the form of agricultural, forestry, and fisheries subsidies — $274–542 billion per year in 2019 — are two to four times higher than annual capital flows toward biodiversity conservation.” (Deutz et al, 2020, page 12).

Finally, the third factor contributing to the failure of the Aichi targets was the lack of government commitment, inadequate monitoring and reporting by the CBD, and low public awareness. These factors combined to weaken stakeholder engagement, resulting in limited societal pressure for action.

**Kunming-Montreal Global Biodiversity Framework** The failure of the Strategic Plan for Biodiversity 2011–2020 and its Aichi Biodiversity Targets created an urgent need for a more effective global approach. At CBD COP15 in December 2022, 192 countries responded by adopting the Kunming-Montreal Global Biodiversity Framework (GBF). This new framework aims to re-launch global biodiversity conservation efforts by addressing the gaps in national ambition and commitment, as well as previous initiatives. The GBF text is divided into several sections, the most important of which are Section F (2050 vision and 2030 mission), Section G (global goals for 2050) and Section H (global targets for 2030). According to Convention on Biological Diversity (2022), the vision of the Kunming-Montreal Global Biodiversity Framework is “a world of living in harmony with nature where by 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people.” The four 2020 goals are to protect and restore (goal A), prosper with nature (goal B), share benefits fairly (goal C), and invest and collaborate (goal D). While the first three goals are easy to understand, the fourth goal is described as follows:

> “Adequate means of implementation, including financial resources, capacity-building, technical and scientific cooperation, and access to and transfer of technology to fully implement the Kunming-Montreal Global Biodiversity Framework are secured and equitably accessible to all Parties, especially developing country Parties, in particular the
<table><caption>Table 5.71: The 23 targets of the Kunming-Montreal Global Biodiversity Framework</caption><thead><tr><th>Target</th><th>Purpose</th></tr></thead><tbody><tr><td>1</td><td>Plan and manage all areas to reduce biodiversity loss</td></tr><tr><td>2</td><td>Restore 30% of all degraded ecosystems — terrestrial, inland water, and marine and coastal ecosystems</td></tr><tr><td>3</td><td>Conserve 30% of land, waters and seas — protected areas and other effective area-based conservation measures</td></tr><tr><td>4</td><td>Halt species extinction, protect genetic diversity, and manage human-wildlife conflicts</td></tr><tr><td>5</td><td>Ensure sustainable, safe and legal harvesting and trade of wild species (reducing the risk of pathogen spillover)</td></tr><tr><td>6</td><td>Reduce the introduction of invasive alien species by 50% and minimize their impact — eradicating or controlling invasive alien species, especially in priority sites, such as islands</td></tr><tr><td>7</td><td>Reduce pollution to levels that are not harmful to biodiversity — (a) reducing excess nutrients lost to the environment by at least half, (b) reducing the overall risk from pesticides and highly hazardous chemicals by at least half, (c) preventing, reducing, and working towards eliminating plastic pollution</td></tr><tr><td>8</td><td>Minimize the impacts of climate change on biodiversity and build resilience</td></tr><tr><td>9</td><td>Manage wild species sustainably to benefit people</td></tr><tr><td>10</td><td>Enhance biodiversity and sustainability in agriculture, aquaculture, fisheries, and forestry</td></tr><tr><td>11</td><td>Restore, maintain and enhance nature's contributions to people</td></tr><tr><td>12</td><td>Enhance green spaces and urban planning for human well-being and biodiversity</td></tr><tr><td>13</td><td>Increase the sharing of benefits from genetic resources, digital sequence information and traditional knowledge</td></tr><tr><td>14</td><td>Integrate biodiversity in decision-making at every level</td></tr><tr><td>15</td><td>Businesses assess, disclose and reduce biodiversity-related risks and negative impacts</td></tr><tr><td>16</td><td>Enable sustainable consumption choices to reduce waste and overconsumption</td></tr><tr><td>17</td><td>Strengthen biosafety and distribute the benefits of biotechnology</td></tr><tr><td>18</td><td>Reduce harmful incentives by at least $500 billion per year, and scale up positive incentives for biodiversity</td></tr><tr><td>19</td><td>Mobilize $200 billion per year for biodiversity from all sources, including $30 billion through international finance</td></tr><tr><td>20</td><td>Strengthen capacity-building, technology transfer, and scientific and technical cooperation for biodiversity</td></tr><tr><td>21</td><td>Ensure that knowledge is available and accessible to guide biodiversity action</td></tr><tr><td>22</td><td>Ensure participation in decision-making and access to justice and information related to biodiversity for all</td></tr><tr><td>23</td><td>Ensure gender equality and a gender-responsive approach for biodiversity action</td></tr></tbody></table>

Source: (Convention on Biological Diversity, 2022, pages 9–13).
least developed countries and small island developing States, as well as countries with
economies in transition, progressively closing the biodiversity finance gap of $700 billion
per year, and aligning financial flows with the Kunming-Montreal Global Biodiversity
Framework and the 2050 Vision for biodiversity." (Convention on Biological Diversity,
2022, page 9).

Table 5.71 shows the 23 targets. At first glance, one might get the impression that the Kunming-Montreal targets are close to the Aichi targets. This is true, and we also note that some targets are always vague. However, if the official text is not technical, the CBD has done some work since its publication to be more precise. In fact, the guidelines for these targets, the indicators for monitoring progress and the national targets submitted to the CBD Secretariat are available on the website www.cbd.int/gbf/targets. For each target, we can find the following guidance notes prepared by the Secretariat:

A. Why is this target important?

B. Explanation of the target and its elements

C. Links to other elements of the Kunming-Montreal GBF, and other frameworks and processes

D. Guiding questions to national-setting

E. Indicators

F. Relevant resources that can assist implementation

Concerning indicators, they are split into three categories: headline indicators<fnref n="221" />, component indi-
cators and complementary indicators. For example, if we consider Target 6 on invasive alien species,
there is one headline indicator (rate of invasive alien species establishment), three component indi-
cators (rate of invasive alien species impact and rate of impact; rate of invasive alien species spread;
number of invasive alien species introductions) and three complementary indicators (number of inva-
sive alien species on national lists; trends in abundance, temporal occurrence and spatial distribution
of non-indigenous species; Red List Index (impact of invasive alien species)).

A major challenge in implementing the Kunming-Montreal GBF is financing. Goal D of the GBF recognized a current biodiversity finance gap of $700 billion per year. To address this, Target 18 proposes to reduce incentives and subsidies that harm biodiversity by $500 billion per year by 2030,

<footnote n="221">²²¹Here are all the headline indicators identified by the CBD Secretariat as of March 2025: 1.A.1 Red List of ecosystems; 1.A.2 Extent of natural ecosystems; 1.1 Per cent of land and seas covered by biodiversity-inclusive spatial plans; 2.2 Area under restoration; 3.1 Coverage of protected areas and OECMs; 4.A.3 Red list Index; 4.A.4 The proportion of populations within species with an effective population size > 500; 5.1 Proportion of fish stocks within biologically sustainable levels; 6.1 Rate of invasive alien species establishment; 7.1 Index of coastal eutrophication potential; 7.2 Pesticide environment concentration; 9.1 Benefits from the sustainable use of wild species; 9.2 Percentage of the population in traditional occupations; 10.1 Proportion of agricultural area under productive and sustainable agriculture; 10.2 Progress towards sustainable forest management; 11.B.1 Services provided by ecosystems; 12.1 Average share of the built-up area of cities that is green/blue space for public use for all; 13.C.1 Indicator on monetary benefits received; 13.C.2 Indicator on non-monetary benefits; 15.1 Number of companies reporting on disclosures of risks, dependencies and impacts on biodiversity; 18.1 Positive incentives in place to promote biodiversity conservation and sustainable use; 19.D.1 International public funding, including official development assistance for conservation and sustainable use of biodiversity and ecosystems; 19.D.2 Domestic public funding of conservation and sustainable use of biodiversity and ecosystems; 19.D.3 Private funding (domestic and international) of conservation and sustainable use of biodiversity and ecosystems; 21.1 Indicator on biodiversity information for monitoring the global biodiversity framework. The first number is the GBF target number. Note that headline indicators have not yet been identified for some targets.</footnote>
while Target 19 specifies that at least $200 billion per year needs to be mobilized by 2030 to implement national biodiversity strategies. The latter target includes increasing financial resources from developed countries, providing development assistance to developing countries, leveraging private finance, promoting blended finance, encouraging impact funds, and promoting innovative schemes such as payments for ecosystem services, green bonds, biodiversity offsets and credits, and benefit-sharing mechanisms. As previously noted, Deutz et al (2020) estimated biodiversity funding at $124-143 billion per year in 2019, with the breakdown shown in Table 5.72. 57% and 20% are financed through domestic budgets and natural infrastructure, respectively. Green financial products, such as green bonds and nature-based solutions, account for less than 3%. Using the OECD's category of potential biodiversity subsidies, the authors estimated global harmful subsidies to be between $274 and $542 billion per year in 2019.

<table><caption>Table 5.72: Global biodiversity conservation financing in 2019 (in $ bn)</caption><thead><tr><th>Financial flows</th><th>Lower limit</th><th>Upper limit</th><th>Midpoint</th><th>Percentage</th></tr></thead><tbody><tr><td>Domestic budgets and tax policy</td><td>74.6</td><td>77.7</td><td>76.2</td><td>57.1%</td></tr><tr><td>Natural infrastructure</td><td>26.9</td><td>26.9</td><td>26.9</td><td>20.2%</td></tr><tr><td>Biodiversity offsets</td><td>6.3</td><td>9.2</td><td>7.8</td><td>5.8%</td></tr><tr><td>Sustainable supply chains</td><td>5.5</td><td>8.2</td><td>6.8</td><td>5.1%</td></tr><tr><td>Official development assistance (ODA)</td><td>4.0</td><td>9.7</td><td>6.8</td><td>5.1%</td></tr><tr><td>Green financial products</td><td>3.8</td><td>6.3</td><td>5.0</td><td>3.8%</td></tr><tr><td>Philanthropy & conservation NGOs</td><td>1.7</td><td>3.5</td><td>2.6</td><td>2.0%</td></tr><tr><td>Nature-based solutions & carbon markets</td><td>0.8</td><td>1.4</td><td>1.1</td><td>0.8%</td></tr><tr><td>Total</td><td>123.6</td><td>142.9</td><td>133.3</td><td>100.0%</td></tr></tbody></table>

Source: Deutz et al (2020, Table 3.1, page 48).

Estimated funding needs are reported in Table 5.73. Croplands and protected areas account for 64% of total funding, while fisheries and forest conservation accounts for only 7% of total funding (about $60 billion per year). Deutz et al (2020) proposed nine financial and policy mechanisms to reduce the biodiversity financing gap. The optimistic estimate is a total positive financial flow of $632.5 billion, which is insufficient to close the gap (Table 5.74). While significant progress has been made since 2022 (establishment of the Global Biodiversity Framework Fund (GBFF), launch of the Cali Fund), we are still not on track to meet the 23 goals of the Kunming-Montreal Global Biodiversity Framework.

<table><caption>Table 5.73: Global biodiversity conservation funding needs (in $ bn)</caption><thead><tr><th>Funding needs</th><th>Lower limit</th><th>Upper limit</th><th>Midpoint</th><th>Percentage</th></tr></thead><tbody><tr><td>Croplands</td><td>315</td><td>420</td><td>367.5</td><td>43.5%</td></tr><tr><td>Protected areas</td><td>149</td><td>192</td><td>170.5</td><td>20.2%</td></tr><tr><td>Rangelands</td><td>81</td><td>81</td><td>81.0</td><td>9.6%</td></tr><tr><td>Urban environments</td><td>73</td><td>73</td><td>73.0</td><td>8.6%</td></tr><tr><td>Invasive alien species</td><td>36</td><td>84</td><td>60.0</td><td>7.1%</td></tr><tr><td>Coastal</td><td>27</td><td>37</td><td>32.0</td><td>3.8%</td></tr><tr><td>Fisheries</td><td>23</td><td>47</td><td>35.0</td><td>4.1%</td></tr><tr><td>Forests</td><td>19</td><td>32</td><td>25.5</td><td>3.0%</td></tr><tr><td>Total</td><td>722</td><td>967</td><td>844.5</td><td>100.0%</td></tr></tbody></table>

Source: Deutz et al (2020, Figure 4.1, page 55).
<table><caption>Table 5.74: Estimated positive and negative flows to biodiversity conservation (in $ bn)</caption><thead><tr><th rowspan="2">Financial flows</th><th colspan="2">2019</th><th colspan="2">2030</th></tr><tr><th>Lower limit</th><th>Upper limit</th><th>Lower limit</th><th>Upper limit</th></tr></thead><tbody><tr><td>Harmful subsidy reform</td><td>-542.0</td><td>-273.9</td><td>-268.1</td><td>0.0</td></tr><tr><td>Domestic budgets and tax policy</td><td>74.6</td><td>77.7</td><td>102.9</td><td>155.4</td></tr><tr><td>Natural infrastructure</td><td>26.9</td><td>26.9</td><td>104.7</td><td>138.6</td></tr><tr><td>Biodiversity offsets</td><td>6.3</td><td>9.2</td><td>162.0</td><td>168.0</td></tr><tr><td>Sustainable supply chains</td><td>5.5</td><td>8.2</td><td>12.3</td><td>18.7</td></tr><tr><td>Official development assistance (ODA)</td><td>4.0</td><td>9.7</td><td>8.0</td><td>19.4</td></tr><tr><td>Green financial products</td><td>3.8</td><td>6.3</td><td>30.9</td><td>92.5</td></tr><tr><td>Philanthropy & conservation NGOs</td><td>1.7</td><td>3.5</td><td></td><td></td></tr><tr><td>Nature-based solutions & carbon markets</td><td>0.8</td><td>1.4</td><td>24.9</td><td>39.9</td></tr><tr><td>Total</td><td>123.6</td><td>142.9</td><td>445.7</td><td>632.5</td></tr></tbody></table>

Source: Deutz et al (2020, Figure 5.1, page 64).

## IPBES

Established in 2012, the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) is an international organization that assesses the state of the world's biodiversity and ecosystem services. It plays a similar role for biodiversity as the Intergovernmental Panel on Climate Change (IPCC) does for global warming. The current staff of the IPBES Secretariat is employed by UNEP and located in Bonn, Germany. In addition, about 2900 experts participate or have participated in the work of IPBES. Its main functions are to provide comprehensive scientific assessments of the state of biodiversity and ecosystem services, to support policy development and implementation, and to identify key scientific information needed for policymakers. The organization has gained international recognition primarily through its influential assessment reports. As of March 2025, it has produced 13 assessment reports:

* Global reports

- Global assessment report on biodiversity and ecosystem services (2019)

* Thematic reports

- Pollinators, pollination and food production (2016)

- Land degradation and restoration (2018)

- Sustainable use of wild species (2022)

- Invasive alien species and their control (2023)

- Interlinkages among biodiversity, water, food and health (2024)

* Methodological reports

- Scenarios and models of biodiversity and ecosystem services (2016)

- The diverse values and valuation of nature (2022)

- Underlying causes of biodiversity loss and the determinants of transformative change and options for achieving the 2050 Vision for Biodiversity (2024)
* Regional reports

- Biodiversity and ecosystem services for Africa (2018)

- Biodiversity and ecosystem services for the Americas (2018)

- Biodiversity and ecosystem services for Asia and the Pacific (2018)

- Biodiversity and ecosystem services for Europe and Central Asia (2018)

In addition, four new assessment reports will be published in the coming years: Impact and dependence of business on biodiversity and nature's contributions to people (2025); Monitoring biodiversity and nature's contributions to people (2026); Integrated biodiversity-inclusive spatial planning and ecological connectivity (2027); Second global assessment of biodiversity and ecosystem services (2028).

<figure><img src="image_262.png" /><figcaption>Figure 5.109: Some IPBES assessment reports</figcaption></figure>

Source: IPBES & www.ipbes.net/assessing-knowledge.

TNFD

The Taskforce on Nature-related Financial Disclosures is a global initiative to develop a framework for companies and financial institutions to report and act on nature-related risks and opportunities. Officially launched in 2021 by four founding organizations (Global Canopy, UNDP, UNEP FI and WWF), the TNFD differs from the TCFD in that it is not supported by the Financial Stability Board (FSB) or any other international regulatory body. Instead, it is a market-driven initiative supported by national governments, corporations and financial institutions. The 40 members of the Taskforce are senior executives from financial institutions (17), corporations (17) and market service providers (6). In April 2024, the ISSB and TNFD announced joint research projects on risks and opportunities related to nature and human capital. However, there are currently no plans to integrate the TNFD framework into the ISSB's sustainability standards (IFRS S1 and IFRS S2).

TNFD uses the same structure as TCFD, organized into four pillars: Governance, Strategy, Risk & impact management, and Metrics & targets. The TNFD framework is based on 14 recommended disclosures, 11 of which are carried over from the TCFD framework (Table 5.75). The three additional recommended disclosures are (3) engagement with indigenous peoples, local communities (IPLC) and affected stakeholders, (7) disclosure of the location of assets and activities in direct operations and, where possible, in the upstream/downstream value chain, and (9) identification and
assessment of nature-related dependencies in the upstream/downstream value chain. According to TNFD (2023), the framework is consistent with ISSB and GRI standards, and is aligned with Target 15 of the Kunming-Montreal GBF. In addition, the TNFD has developed guidance for some specific sectors (e.g., aquaculture, beverages, metals and mining, chemicals) and the following biomes: tropical and sub-tropical forests, savannas and grasslands, intensive land-use systems, urban and industrial ecosystems, rivers and streams, and marine shelf. Two types of indicators are included in TNFD:

* A small set of core indicators (global core indicators applicable to all sectors and sector core indicators for each sector)

* A large set of additional disclosure and assessment indicators (optional)

In TNFD (2023), there are 14 global core indicators, including 9 indicators for nature-related dependencies and impacts (Table 5.76) and 5 indicators for nature-related risks and opportunities (Table 5.77). In addition, TNFD (2023) introduces several additional global and sector-specific indicators<fnref n="222" />.

<table><caption>Table 5.75: The 14 recommended disclosures (TNFD, 2023)</caption><thead><tr><th>Pillar</th><th>#</th><th>Recommended Disclosure</th></tr></thead><tbody><tr><td rowspan="3">Governance</td><td>1</td><td>Board oversight</td></tr><tr><td>2</td><td>Management's role</td></tr><tr><td>3</td><td>Human rights policies (IPLC)</td></tr><tr><td rowspan="5">Strategy</td><td>4</td><td>Risks and opportunities</td></tr><tr><td>5</td><td>Impact on organization</td></tr><tr><td>6</td><td>Resilience of strategy</td></tr><tr><td>7</td><td>Locations of assets/activites/value chain</td></tr><tr><td>8</td><td>Risk identification and assessment processes</td></tr><tr><td rowspan="4">Risk management</td><td>9</td><td>Dependencies in the value chain</td></tr><tr><td>10</td><td>Risk management processes</td></tr><tr><td>11</td><td>Integration into overall risk management</td></tr><tr><td>12</td><td>Nature-related metrics</td></tr><tr><td rowspan="2">Metrics and targets</td><td>13</td><td>Metrics used to manage impacts and risks</td></tr><tr><td>14</td><td>Nature-related targets</td></tr></tbody></table>

Source: TNFD (2023) & https://tnfd.global.

As of October 2024, there are 502 TNFD adopters, including 318 corporations and 129 financial institutions. The majority are located in Asia (236) and Europe (183). These adopters represent $17.7 trillion in assets under management and $6.5 trillion in market capitalization.

## European biodiversity framework

The EU Biodiversity Strategy for 2030 was published in May 2020 and is part of the European Green Deal to tackle the ongoing biodiversity loss crisis. It replaces the Biodiversity strategy for 2020. The overall goal is to restore biodiversity and healthy ecosystems across the EU. Examples of quantitative targets include planting 3 billion trees by 2030, restoring 25 000 km of free-flowing rivers by removing barriers, increasing organic farming to 25% of agricultural land, and reducing

<footnote n="222">²²²These can be found in TNFD (2023, Annex 2, pages 89–99) and Section 3 of the various sector guidance documents.</footnote>
<table><caption>Table 5.76: TNFD core global disclosure indicators for nature-related dependencies and impacts</caption><thead><tr><th>#</th><th>Indicator</th><th>Unit</th><th>GBF Targets</th></tr></thead><tbody><tr><td>C1.0</td><td>Total spatial footprint</td><td>km<sup>2</sup></td><td>1, 2, 5, 11</td></tr><tr><td>C1.1</td><td>Extent of land/freshwater/ocean-use change</td><td>km<sup>2</sup></td><td>1, 2, 5, 11</td></tr><tr><td>C2.0</td><td>Pollutants released to soil split by type</td><td>tonne</td><td>7, 11</td></tr><tr><td>C2.1</td><td>Wastewater discharged</td><td>m<sup>3</sup></td><td>7, 11</td></tr><tr><td>C2.2</td><td>Waste generation and disposal</td><td>m<sup>3</sup></td><td>7, 11</td></tr><tr><td>C2.3</td><td>Plastic pollution</td><td>tonne</td><td>7, 11</td></tr><tr><td>C2.4</td><td>Non-GHG air pollutants</td><td>PM<sub>2.5</sub>, etc.</td><td>7, 11</td></tr><tr><td>C3.0</td><td>Water withdrawal and consumption from areas of water scarcity</td><td>m<sup>3</sup></td><td>11</td></tr><tr><td>C3.1</td><td>Quantity of high-risk natural commodities sourced from land/ocean/freshwater</td><td>tonne</td><td>5, 9, 11</td></tr><tr><td>C4.0</td><td>Measures against unintentional introduction of invasive alien species</td><td></td><td>6, 11</td></tr><tr><td>C5.0</td><td>Ecosystem condition</td><td></td><td>1, 2, 3, 4, 11</td></tr><tr><td>C5.0</td><td>Species extinction risk</td><td></td><td>1, 2, 3, 4, 11</td></tr></tbody></table>

<table><caption>Table 5.77: TNFD core global disclosure indicators for nature-related risks and opportunities</caption><thead><tr><th>#</th><th>Indicator</th></tr></thead><tbody><tr><td>C7.0</td><td>Value of assets, liabilities, revenue and expenses that are assessed as vulnerable to nature-related transition risks (total and proportion of total)</td></tr><tr><td>C7.1</td><td>Value of assets, liabilities, revenue and expenses that are assessed as vulnerable to nature-related physical risks (total and proportion of total)</td></tr><tr><td>C7.2</td><td>Description and value of significant fines/penalties received/litigation action in the year due to negative nature-related impacts</td></tr><tr><td>C7.3</td><td>Amount of capital expenditure, financing or investment deployed towards nature-related opportunities, by type of opportunity, with reference to a government or regulator green investment taxonomy or third-party industry or NGO taxonomy, where relevant</td></tr><tr><td>C7.4</td><td>Increase and proportion of revenue from products and services producing demonstrable positive impacts on nature with a description of impacts</td></tr></tbody></table>

<table><caption>Table 5.78: Examples of TNFD additional global disclosure indicators</caption><thead><tr><th>#</th><th>Indicator</th></tr></thead><tbody><tr><td>A2.3</td><td>Light and noise pollution</td></tr><tr><td>A3.4</td><td>Area used for the production of natural commodities</td></tr><tr><td>A3.5</td><td>Use of wild species</td></tr><tr><td>A4.0</td><td>Number/extent of unintentionally introduced species, varieties or strains</td></tr><tr><td>A7.0</td><td>Value of write-offs and early retirements of assets due to nature-related risks</td></tr><tr><td>A8.4</td><td>Capital expenditure on adaption due to nature-related physical risks</td></tr><tr><td>A20.0</td><td>Proportion of sites that have active engagement with local stakeholders on nature-related issues</td></tr></tbody></table>

Source: TNFD (2023, Tables 6–10, pages 83–99).
pesticide use by 50%. In June 2022, the European Commission also adopted a proposal for a Nature Restoration Law. EU member states will have to develop their national restoration plans by 2026 with the following objectives: restore at least 30% of habitats in poor condition by 2030, 60% by 2040, and 90% by 2050. Since then, two guidelines on forest and soil monitoring have been published in 2023. In the coming years, we can expect new biodiversity laws and regulations in the European Union, following the establishment of the EU Biodiversity Platform (EUBP) in 2022. The platform currently consists of 10 working groups addressing various biodiversity issues<fnref n="223" />.

### 5.4.6 Investment approaches

While ESG and climate investing are now two mainstream investment approaches in asset management, the concept of biodiversity investing is relatively new. In fact, the term 'biodiversity finance' is generally more appropriate, as it encompasses a broader range of financial instruments beyond investment practices. Nevertheless, the field of biodiversity investing is developing rapidly. For example, with the exception of BIOFIN, which was launched by UNDP in 2012 following the CBD COP10 in Nagoya in 2010, most of the major biodiversity-focused financial initiatives and alliances have been created more recently, particularly following the One Planet Summit or the CBD COP15 in 2022 (Table 5.79). This also explains why biodiversity investing is a relatively new topic for academics<fnref n="224" />, as most of the existing literature is in the gray area (Hutchinson and Lucey, 2024).

<table><caption>Table 5.79: Biodiversity finance initiatives</caption><thead><tr><td>Acronym</td><td>Name</td><td>Website</td><td>Year</td></tr></thead><tbody><tr><td>BCA</td><td>Biodiversity Credit Alliance</td><td>www.biodiversitycreditalliance.org</td><td>2022</td></tr><tr><td>BIOFIN</td><td>Biodiversity Finance Initiative</td><td>www.biofin.org</td><td>2012</td></tr><tr><td>BfN</td><td>Business for Nature</td><td>www.businessfornature.org</td><td>2019</td></tr><tr><td>FfB</td><td>Finance for Biodiversity Foundation</td><td>www.financeforbiodiversity.org</td><td>2021</td></tr><tr><td>NCIA</td><td>Natural Capital Investment Alliance</td><td>www.sustainable-markets.org</td><td>2021</td></tr><tr><td>NA 100</td><td>Nature Action 100</td><td>www.natureaction100.org</td><td>2023</td></tr></tbody></table>

**Remark 70** Biodiversity finance can include economic and financial instruments that are not related to the concepts of biodiversity investing. For example, most OECD research and publications on biodiversity finance focus on public finance, policy instruments such as taxes, subsidies or payments for ecosystem services.

#### Financial instruments

The Global Biodiversity Framework considers that the private sector is essential to achieve the 2050 Vision for Biodiversity, not just the public sector. For instance, the private sector is mentioned in several targets. Thus, Target 15 requires large companies and financial institutions to monitor, assess, and disclose biodiversity risks. Target 19 states that private resources must be mobilized by "leveraging private finance, promoting blended finance, implementing strategies for raising new and additional resources, and encouraging the private sector to invest in biodiversity, including

<footnote n="223">²²³These are (1) Working group on forests and nature; (2) Invasive alien species expert group; (3) Sub-group on monitoring and assessment; (4) Working group on green infrastructure; (5) Working group on invasive alien species; (6) Commission expert group on the birds and habitats directives; (7) Marine issues; (8) Reporting under the nature directives; (9) Expert group on the nature restoration regulation; (10) Working group on pollinators.</footnote>

<footnote n="224">²²⁴Recent academic research on biodiversity investing includes Giglio et al (2023b), Flammer et al (2025), Cherief et al (2025), and Coqueret et al. (2025).</footnote>
*through impact funds and other instruments.*” To better understand biodiversity investing from the perspective of private investors, one approach is to list the different instruments that fit into this category. Here is a classification of the main instruments:

• Fixed-income instruments

- Blue bonds

*Definition* Debt securities designed to raise capital for marine and ocean conservation projects (e.g., protecting marine biodiversity, restoring coastal ecosystems, financing sustainable fisheries)

*Example* Seychelles Blue Bond (2018), which raised $15 million to support sustainable marine areas and fisheries

- Debt-for-nature swaps

*Definition* Financial transactions in which a portion of a country's debt is forgiven in exchange for environmental commitments

*Example* Gabon debt-for-nature swap (2023), which restructured $500 million of debt to protect 30% of marine and forest ecosystems

- Green and sustainable bonds

*Definition* Debt instruments that target environmental projects and sustainable land use

*Example* Colombia Biodiversity Bond (BBVA/IFC), which raised $50 million to finance projects focused on reforestation and wildlife habitat restoration

- Natural capital bonds, nature performance bonds and conservation performance bonds

*Definition* Bonds that directly finance the protection and restoration of natural capital, with returns linked to specific ecological performance metrics and biodiversity outcomes, or that monetize the value of ecosystem services and biodiversity

*Example* Voluntary carbon credit-linked bonds, such as the IFC Forest Bond

- Sustainability-linked bonds and pay-for-success financial instruments

*Definition* Bonds whose financial characteristics can change based on the achievement of sustainability targets

*Example* Rhino Bond (2022), issued by the World Bank ($150 million), where returns are linked to the growth of the black rhino population in Africa

• Market-based instruments

- Biodiversity credits/offsets

*Definition* tradable units representing positive biodiversity outcomes (market mechanisms to promote biodiversity conservation)

*Example* UK Biodiversity Net Gain (BNG) policy (developers must ensure a 10% net gain in biodiversity by funding conservation projects or purchasing biodiversity credits)

- Nature-based insurance products

*Definition* Insurance mechanisms to protect natural capital and ecosystem services

*Example* Parametric insurance for coral reef protection in the Caribbean and Central America (provides insurance coverage for coastal infrastructure and triggers payouts for reef restoration after hurricanes)
- Payments for ecosystem services (PES)

*Definition* Schemes that provide financial incentives to landowners or communities to manage their land in a way that maintains or enhances ecosystem services

*Example* Vittel (Nestlé Waters) offers PES to farmers in the Vosges mountains in France to maintain water quality

* Investment funds

- Biodiversity impact funds

*Definition* Specialized investment vehicles focused on biodiversity conservation

*Example* The African Forestry Impact Platform (AFIP) managed by Norfund, which invests in sustainable forestry and conservation projects

- Blended finance

*Definition* Combines public and private capital to attract more capital to biodiversity projects

*Example* The Land Degradation Neutrality (LDN) Fund initiated by the United Nations Convention to Combat Desertification (UNCCD) and Mirova, which finances the rehabilitation of degraded land

- Conservation trust funds

*Definition* Long-term financing mechanisms for conservation and sustainable development

*Example* Bhutan Trust Fund for Environmental Conservation (BTFEC)

- Private equity and venture capital funds

*Definition* Investment funds focused on companies and technologies that support biodiversity

*Example* Regeneration VC Fund

## The avoid-minimize-restore-offset approach

To effectively integrate biodiversity into investment processes, it is essential to understand the mitigation hierarchy, a fundamental principle of conservation biology (Arlidge et al, 2018). The mitigation hierarchy is a structured framework to guide decision-making in managing environmental impacts. It prioritizes actions to avoid, minimize, restore, and offset negative impacts on biodiversity (Figure 5.110). Avoid prevents negative impacts on biodiversity before they occur. This step emphasizes avoiding environmentally harmful activities and encourages decision-makers to choose alternative actions or project designs that have no or minimal adverse effects on biodiversity. For example, this might involve selecting a project site that is not located in a critical habitat or a biodiversity hotspot. Minimize aims to reduce the impact of unavoidable harm to biodiversity as much as possible by decreasing the magnitude, duration and/or intensity of potential impacts when they cannot be avoided completely. An example is implementing construction practices that reduce habitat destruction, such as minimizing land clearing or avoiding key wildlife breeding seasons. Restore focuses on rehabilitating ecosystems that have been damaged by development activities. This can include replanting trees in areas affected by deforestation, restoring native vegetation, or rebuilding habitat structures to support local ecological systems. Finally, if residual impacts remain after avoid, minimize, and restore measures, offsets are used to compensate for the remaining losses. This involves creating or enhancing biodiversity elsewhere to achieve no net loss or a net gain in ecological value.
<figure><img src="image_263.png" /><figcaption>Figure 5.110: Mitigation hierarchy for nature conservation</figcaption></figure>

By construction, the mitigation hierarchy is an impact approach where we assess how companies and investments impact biodiversity. From a financial perspective, it is equally important to consider how companies and investments are affected by biodiversity loss. In this context, we can adopt a dependency approach based on four key risk dimensions: transition risk, physical risk, litigation risk and systemic risk. For instance, some sectors or companies are highly dependent on raw materials, soil productivity, or freshwater. As a result, loss of biodiversity can create physical risk directly or indirectly through the supply chain. Transitional risk can arise from new or emerging regulations and changes in consumer preferences. Litigation risk arises when companies face potential legal challenges related to environmental damage, failure to protect biodiversity, or non-compliance with environmental regulations. Such risks can result in significant financial penalties, reputational damage and lawsuits. The final category of risk is systemic risk, which affects companies indirectly. For example, they may be affected by severe pandemics that disrupt global ecosystems and economic systems. This dual perspective of biodiversity risk refers to the double materiality principle:

<table><thead><tr><th colspan="2">Double materiality principle</th></tr></thead><tbody><tr><td>Dependency</td><td>How does biodiversity affect companies and investments?</td></tr><tr><td>Impact</td><td>How do companies and investments affect biodiversity?</td></tr></tbody></table>

Applying the avoid dimension of the mitigation hierarchy to investments requires the adoption of negative screening and the establishment of exclusion criteria for issuers or projects that significantly harm biodiversity. The minimize dimension can be effectively implemented through best-in-class strategies or selective approaches that prioritize companies with stronger biodiversity practices. A key challenge in this dimension is the development and use of biodiversity metrics that appropriately
account for both sector-specific impacts and geographic contexts, as the importance of biodiversity varies widely across ecosystems. For the restore/offset dimension, the focus shifts to creating positive impacts. Traditional avoidance and minimization metrics prove inadequate here, as these final stages require the identification and selection of companies and projects that have a positive biodiversity footprint. This requires a different set of metrics that focus on restoration outcomes, additionality and measurable biodiversity gains. For example, an MSA metric is not relevant to this dimension. As a result, each progression through the hierarchy requires increasingly sophisticated measurement approaches, moving from harm reduction to positive contribution assessment.

<figure><img src="image_264.png" /><figcaption>Figure 5.111: Linking ESG investment strategies and biodiversity mitigation dimensions</figcaption></figure>

## The impact investing approach

According to Phenix Capital (2024b), the biodiversity impact fund landscape appears robust, with 1080 biodiversity-related funds and a market size of €129 billion in open-end investment funds. At first glance, these figures appear substantial, especially when compared to the investment required to meet the targets of the GBF. However, a deeper analysis reveals a more nuanced picture. A striking 69% of these funds primarily address food-related needs rather than direct biodiversity conservation. When focusing specifically on funds targeting SDG 14 (life below water) and SDG 15 (life on land), the numbers drop to 162 and 278 impact funds, respectively. Real assets and private equity dominate these specialized sectors, accounting for 33% and 30% of these biodiversity-focused funds, respectively. However, the geographic and thematic distribution reveals significant gaps.
Only 11 real asset impact funds focus on timber and forests in Asia, 12 in Africa, and 26 in South America — regions that contain much of the world’s remaining primary biodiversity. This creates a paradox. While the aggregate numbers suggest impressive financial mobilization for biodiversity, an examination of specific critical issues, such as forest conservation, reveals low investment volumes.

## 5.5 Exercises

### 5.5.1 Calculating the prevalence of undernourishment

Let $X$ and $R$ be the random variables representing energy intake and energy requirement, respectively.

1. We assume that the random vector $(X, R)$ follows a bivariate log-normal distribution: $(X, R) \sim \mathcal{LN}(\mu_x, \sigma_x^2, \mu_r, \sigma_r^2, \rho)$.

(a) Find the probability distribution of $D = X/R$. Then, calculate the prevalence of under-nourishment, denoted by $PoU^* = \text{Pr}\{X < R\}$.

(b) Assume that $\mu_x = 7.50$, $\sigma_x = 0.20$, $\mu_r = 7.20$, and $\sigma_r = 0.05$. Plot the density functions of $X$ and $R$.

(c) Plot the function of $PoU^*$ as $\rho$ varies in the interval $[-1, 1]$. Comment on the results.

(d) Compute the prevalence of undernourishment defined by $PoU = \text{Pr}\{X < r_L\}$. Plot the relationship between $r_L$ and $PoU$ when $r_L \in [1000, 1600]$.

(e) Find the value of $r_L^*$ such as $PoU = PoU^*$. Calibrate the parameter $r_L^*$ for the prevalence of undernourishment calculated in Question 1.c.

2. We want to calibrate the probability distribution function of $X$. We assume that $X \sim \mathcal{LN}(\mu_x, \sigma_x^2)$.

(a) Give the first two moments of $X$. We will denote them by $\mu(X)$ and $\sigma^2(X)$.

(b) Deduce the coefficient of variation $CV(X)$.

(c) Find the moment estimators of $\mu_x$ and $\sigma_x$ from $\mu(X)$ and $CV(X)$.

(d) We consider an hypothetical country with a population of 1 million and two food components (cereals and fruits/vegetables), whose the food balance sheet is as follows:

<table><thead><tr><th></th><th>Production</th><th>Imports</th><th>Exports</th><th>ΔStocks</th><th>Feed</th><th>Waste</th></tr></thead><tbody><tr><td>#1</td><td>349 000</td><td>1 025</td><td>40 000</td><td>-1 000</td><td>45 000</td><td>9 000</td></tr><tr><td>#2</td><td>50 000</td><td>9 010</td><td>1 000</td><td>6 000</td><td>500</td><td>500</td></tr></tbody></table>

All the figures are expressed in tonnes. Calculate the food available for human consumption. Assuming that the average energy density is 3500 and 500 Calories/kg for cereals and fruits/vegetables respectively, find the average dietary energy consumption $\mu(X)$ expressed in kcal/capita/day.

(e) The average dietary energy consumption by household expenditure deciles are 1650 (first decile), 1985, 2150, 2350, 2530, 2550, 2650, 2750, 3100 and 3630 (last decile). Calculate the coefficient of variation $CV(X | Y)$. Check that $\mu(X | Y) = \mu(X)$. Assuming that $CV(X | R) = 0.20$, calculate $CV(X)$.
(f) Calibrate the parameters $\mu_x$ and $\sigma_x$ using the previous figures. What is the prevalence of undernourishment if we assume that $r_L = 1.850$? Give an estimate of the number of undernourished people.

3. We seek to estimate the minimum dietary energy requirement.

(a) We recall that the body mass index (BMI) is expressed in kg/m² and is defined as the ratio of the weight (in kg) to the square of the height (in meter):

$$BMI = \frac{\text{weight}}{\text{height}^2}$$

The ideal value of BMI is 22. To define undernourished people, we assume that their weight is below a reference value:

$$\text{weight} \leq \text{weight}^*$$

where:

$$\text{weight}^* = \text{BMI}(p) \cdot \text{height}^2$$

where $p$ is a percentile value that depends on age. If the age is less than ten years, $p$ is set to 50%, while for individuals 10 years and older, it is set to 5%. Below, we give the values of BMI ($p$) and the average height per age and sex:

<table><thead><tr><th></th><th>Age</th><th>-3</th><th>3-10</th><th>10-18</th><th>18-30</th><th>30-60</th><th>60+</th></tr></thead><tbody><tr><th rowspan="2">BMI (p)</th><td>Female</td><td>15.5</td><td>15.5</td><td>17.0</td><td>17.5</td><td>17.5</td><td>17.5</td></tr><tr><td>Male</td><td>15.5</td><td>15.5</td><td>17.0</td><td>18.5</td><td>18.5</td><td>18.5</td></tr><tr><th rowspan="2">Height</th><td>Female</td><td>0.80</td><td>1.20</td><td>1.55</td><td>1.60</td><td>1.60</td><td>1.60</td></tr><tr><td>Male</td><td>0.88</td><td>1.24</td><td>1.58</td><td>1.72</td><td>1.72</td><td>1.72</td></tr></tbody></table>

Calculate the reference value weight* per age and sex to determine the undernourishment.

(b) We assume that the basal metabolic rate (BMR) is given by the Schofield equation:

$$\text{BMR} = \alpha + \beta \cdot \text{weight}^*$$

where $\alpha_j$ and $\beta_j$ are the estimates of the linear regression between weight and BMR:

<table><thead><tr><th></th><th>Age</th><th>-3</th><th>3-10</th><th>10-18</th><th>18-30</th><th>30-60</th><th>60+</th></tr></thead><tbody><tr><th rowspan="2">α</th><td>Female</td><td>-31.1</td><td>485.9</td><td>692.6</td><td>486.6</td><td>845.6</td><td>658.5</td></tr><tr><td>Male</td><td>-30.4</td><td>504.3</td><td>658.2</td><td>692.2</td><td>873.1</td><td>587.7</td></tr><tr><th rowspan="2">β</th><td>Female</td><td>58.317</td><td>20.315</td><td>13.384</td><td>14.818</td><td>8.126</td><td>9.082</td></tr><tr><td>Male</td><td>59.512</td><td>22.706</td><td>17.686</td><td>15.057</td><td>11.472</td><td>11.711</td></tr></tbody></table>

Calculate the basal metabolic rate for each group.

(c) The minimum dietary energy requirement is equal to the physical activity level (PAL) times the basal metabolic rate:

$$\text{MDER} = \text{PAL} \cdot \text{BMR}$$

We assume that the population is on average lightly active, implying that PAL = 1.55. Calculate the minimum dietary energy requirement for the different groups.
(d) We assume that the proportion of females and males is the same, while the distribution of the population by age is as follows:

<table><thead><tr><th>Age</th><th>-3</th><th>3-10</th><th>10-18</th><th>18-30</th><th>30-60</th><th>60+</th></tr></thead><tbody><tr><th>Frequency</th><td>9.9%</td><td>15%</td><td>16%</td><td>18%</td><td>29%</td><td>12.1%</td></tr></tbody></table>

Calculate the minimum dietary energy requirement of the population.

4. We want to calculate the depth of the food deficit:

$$FD = \int_{x<r_L} (\bar{r} - x) f_x(x) dx$$

where $r_L$ is the minimum dietary energy requirement (MDER), $\bar{r}$ is the average dietary energy requirement (ADER), and $f_x(x)$ is the probability density function of the dietary energy consumption $X$.

(a) What is the interpretation of the indicator FD?

(b) Find the probabilistic expression of the indicator FD.

(c) Find the analytical value of FD when $X \sim LN(\mu_x, \sigma_x^2)$.

(d) Calculate the depth of the food deficit in the case of Question 2 if we assume that the average dietary energy requirement is equal to 2500 Calories per person per day.

### 5.5.2 Calculating the species-area relationship using the theory of island biogeography

1. We consider the model of island biogeography developed by Beaugrand et al. (2024). We denote species richness by $S(t)$. At the initial date $t_0$, we have $S(t_0) = S_0$ (we can assume that $S_0 = 0$). The authors assume the existence of a saturation date $t_s$, i.e., the species richness cannot exceed a limit value:

$$0 \le S(t) \le S_s = S(t_s)$$

(a) Let $f(x) = ae^{b(x/c)^d}$ where $a > 0$, $c > 0$ and $d > 0$. The parameter $b$ can take two values: -1 or +1. We also assume that $0 \le x \le c$. In which case do we get a decreasing, increasing, concave and convex function?

(b) Let $\lambda(t)$ represent the immigration rate. We assume that:

$$\lambda(t) = \lambda_0 \frac{e^{-\left(\frac{S(t)}{S_s}\right)^{\beta_1 \lambda_0}} - e^{-1}}{1 - e^{-1}} \quad \text{for } \lambda_0 \ge \lambda(t) \ge \lambda_s = \lambda(t_s)$$

where $\lambda_0 \ge 0$ is the initial immigration rate, and $\beta_1 > 0$ is a parameter. Prove that $\lambda(t)$ is a decreasing function of $S(t)$, with $\lambda(t_0) = \lambda_0$ and $\lambda(t_s) = 0$. Determine whether $\lambda(t)$ is a convex or concave function. Plot the function $\lambda(t)$ for the following parameter sets ($\lambda_0, \beta_1, S_s$): (1.0, 0.2, 200), (1.0, 0.5, 200), (1.0, 1.0, 200), and (0.9, 2.0, 150). Analyze and comment on these results.
(c) Let $\mu^{\text{long}}(t)$ be the long-term extinction rate. We assume that:

$$ \mu^{\text{long}}(t) = \mu_s \frac{e^{\left(\frac{S(t)}{S_0}\right)^{\beta_2 \mu_s}} - 1}{e^1 - 1} \quad \text{for } \mu_0^{\text{long}} \le \mu^{\text{long}}(t) \le \mu_s = \mu^{\text{long}}(t_s) $$

where $\mu_s \ge 0$ is the extinction rate at the saturation date, and $\beta_2 > 0$ is a parameter. Prove that $\mu^{\text{long}}(t)$ is an increasing function of $S(t)$, with $\mu^{\text{long}}(t_0) = 0$ and $\mu^{\text{long}}(t_s) = \mu_s$. Determine whether $\mu^{\text{long}}(t)$ is a convex or concave function. Plot the function $\mu^{\text{long}}(t)$ for the following parameter sets ($\mu_s, \beta_2, S_s$): (1.0, 0.2, 200), (1.0, 0.5, 200), (1.0, 1.0, 200), and (0.5, 2.0, 150). Analyze and comment on these results.

(d) Let $\mu^{\text{short}}(t)$ be the short-term extinction rate. We assume that:

$$ \mu^{\text{short}}(t) = \beta_3 \lambda(t) e^{-\beta_4 S(t)} \quad \text{for } \mu_0^{\text{short}} \ge \mu^{\text{short}}(t) \ge \mu_s^{\text{short}} = \mu^{\text{short}}(t_s) $$

where $\beta_3$ and $\beta_4$ are two positive parameters. Prove that $\mu^{\text{short}}(t)$ is a decreasing function of $S(t)$, with $\mu^{\text{short}}(t_0) \le \beta_3 \lambda_0$ and $\mu^{\text{short}}(t_s) = 0$. Plot the function$^{225}$ $\mu^{\text{short}}(t)$ for the following parameter sets ($\beta_3, \beta_4, S_s$): (0.2, 0.02, 200), (0.5, 0.02, 200), (0.8, 0.02, 200), and (1.0, 0.10, 150).

(e) Let $\mu(t) = \mu^{\text{short}}(t) + \mu^{\text{long}}(t)$ be the extinction rate. Show that $\mu(t_0) = \mu^{\text{short}}(t_0)$ and $\mu(t_s) = \mu_s$. Plot the function $\mu(t)$ for the following set of parameters: $\lambda_0 = 1$, $\beta_1 = 0.5$, $\mu_s = 1$, $\beta_2 = 2$, $\beta_3 = 0.70$, $\beta_4 = 0.01$, and $S_s = 200$. Comment on these results.

(f) The dynamics of species richness is governed by the following differential equation:

$$ \frac{dS(t)}{dt} = \delta(t) = \lambda(t) - \mu(t) $$

What is the condition for $S(t)$ to reach an equilibrium? Illustrate and determine the equilibrium $S^*$ using the set of parameters provided in Question 1.e.

(g) Under what conditions can two equilibria exist? Let $S_1^*$ and $S_2^*$ be the two equilibria, with $S_1^* \le S_2^*$. Show that $S_1^*$ is an unstable steady state, while $S_2^*$ is a stable steady state. Deduce that there is a third equilibrium $S_0^*$, with $S_0^* \le S_1^* \le S_2^*$. Illustrate the three-equilibrium case with the following set of parameters: $\lambda_0 = 1$, $\beta_1 = 0.5$, $\mu_s = 1$, $\beta_2 = 2$, $\beta_3 = 1.70$, $\beta_4 = 0.02$, and $S_s = 200$.

(h) Using the two sets of parameters defined in Questions 1.e and 1.g, simulate the process $S(t)$ when the initial species richness $S_0$ is 0, 25, 30, 50 and 120, respectively. Comment on these results.

2. We aim to analyze the dynamics of the TIB steady state $S^*$ under the assumption that there is no short-term extinction rate, meaning $\beta_3 = 0$ or $\mu^{\text{short}}(t) = 0$. The default parameter values are $\lambda_0 = 1$, $\beta_1 = 0.5$, $\mu_s = 1$, $\beta_2 = 1$, and $S_s = 200$.

(a) What is the impact of $\beta_2$ on the equilibrium $S^*$? Compare the solutions for $\beta_2 = 0.2$, $\beta_2 = 1$, and $\beta_2 = 5$.

(b) Plot the relationship between $\beta_2$ and $S^*$.

(c) What is the impact of $\mu_s$ on the equilibrium $S^*$?

(d) Plot the relationship between $\mu_s$ and $S^*$.

<footnote>$^{225}$We assume $\lambda_0 = 1.0$ and $\beta_1 = 0.5$ to define $\lambda(t)$.</footnote>
(e) What conclusion can we draw about the relationship between the area A and the equilibrium $S^*$.

(f) We assume that the area A (expressed in km²) is related to the parameter $\beta_2$ as follows: $A = \beta_2^{0.75}$. A sampling of $\beta_2$ is taken between 0.01 and 5.00 with a step size of 0.01. Use nonlinear least squares to estimate the power model $S = cA^z$, the exponential model $S = c + z \ln(A)$, and the Kobayashi model $S = c \ln(1 + zA)$. Compare the TIB equilibrium $S^*$ with the forecasts of the fitted models. Comment on these results.

### 5.5.3 Species abundance models

*Remark: This exercise is inspired by the research articles of Coleman (1981), and He and Legendre (2002).*

1. We consider an area (or an ecosystem) A containing S species. Let $n_i$ denote the abundance of the i-th species and let $n = \sum_{i=1}^{S} n_i$ represent the total abundance in the area. We focus on a subarea $a \subseteq A$ and denote by $\tilde{S}_a$ the random variable representing the number of species in this subarea. We introduce the notation $S_a = \mathbb{E}[\tilde{S}_a]$ to represent the expected number of species in the subarea.

(a) Let $p_i$ be the probability that species i is present in the subarea a, and $\tilde{S}_i \sim \mathcal{B}(p_i)$ the random variable indicating its presence ($\tilde{S}_i = 1$) or its absence ($\tilde{S}_i = 0$). What is the probability distribution of $\tilde{S}_a$? Deduce the value of $S_a$. Application: Given $p = (p_1, \dots, p_5) = (20\%, 30\%, 10\%, 65\%, 10\%)$, calculate $\tilde{S}_a$ and $S_a$.

(b) We assume a random placement of the species within the area A. What is the probability of observing k individuals of species i in the subarea a? Show that:

$$ \tilde{S}_i \sim \mathcal{PB} \left( p_i = 1 - \left(1 - \frac{a}{A}\right)^{n_i} \right) $$

Find the value of $S_a$. Application: Given $(n_1, \dots, n_5) = (10, 4, 25, 6, 8)$, $A = 10 \text{ km}^2$, and $a = 2 \text{ km}^2$, calculate $\tilde{S}_a$ and $S_a$.

(c) Calculate $S_a$ for the following models:

i. Most even model:

$$ n_i = \frac{n}{S} \quad \text{for } i = 1, \dots, S $$

ii. Most uneven model:

$$ n_i = 1 \quad \text{for } i < S \quad \text{and} \quad n_S = n - S + 1 $$

Calculate $\tilde{S}_a$ and $S_a$.

iii. Mixed even-uneven model:

$$ n_i = 1 \quad \text{for } i \le s \quad \text{and} \quad n_i = \frac{n-s}{S-s} = n_{s+1} \quad \text{for } i > s $$

iv. He-Gaston model:

$$ p_i = 1 - \left(1 - \frac{a}{A}\right) \left(1 + \frac{n_i a}{\kappa_i A}\right)^{-\kappa_i} $$

where $\kappa_i \in (-\infty, m_i) \cup [0, \infty)$ is a parameter which describes the spatial pattern of species i and $m_i = n_i a/A$ is the mean density of species i in the subarea a.
v. Broken-stick model<sup>226</sup>:

$$n_i = \frac{n}{S} \sum_{k=i}^{S} \frac{1}{k}$$

(d) The species abundance distribution is defined as the series {$s(1), s(2), \dots$} where $s(j)$ is the number of species with $j$ individuals. Show that:

$$S_a = S - \sum_j s(j) \left(1 - \frac{a}{A}\right)^j$$

Application: Calculate $S_a$ for the log-series distribution:

$$s(j) = \alpha \frac{x^j}{j}$$

where $\alpha$ is a parameter related to the total diversity and $x \in (0, 1)$ is a parameter determining the relative abundance.

2. We say that the species is locally endemic to subarea $a \subseteq A$ if it is found exclusively in subarea $a$ and not in the complementary area $A-a$.

(a) Calculate the probability $\tilde{p}_i$ of endemism of species $i$.

(b) What is the expected number $E_a$ of locally endemic species?

(c) Calculate $S_{A-a}$ and $E_{A-a}$ for the complementary area $A-a$. Deduce that:

$$S_{A-a} + E_a = S$$

(d) Show that:

$$0 \le S_a + E_a \le 2S$$

### 5.5.4 Valuation of risks to life and health

*Remark: This exercise is inspired by the research article of Hammitt (2023).*

Let $\tau$ be a survival time<sup>227</sup>, whose survival function is $S(t) = \Pr\{\tau > t\}$ and density function is $f(t) = -\partial S(t)$. We have $S(0) = 1$ and $S(\infty) = 0$.

1. Assume that the individual is alive at time $t$. What is the conditional survival function $S(u|t) = \Pr\{\tau > u | \tau > t\}$?

2. Show that the average length of life (or life expectancy) for an individual who is alive at time $t$ is given by:

$$\mathrm{LE}(t) = \mathbb{E}[\tau | \tau > t] = \frac{1}{S(t)} \int_{t}^{\infty} S(u) \, du$$

<footnote n="226"><sup>226</sup>Hint: Approximate the harmonic sum by $\ln(\frac{s}{i})$, and replace the sum $\sum_{i=1}^{S} (1 - \frac{a}{A})^{n_i}$ with its integral form.</footnote>

<footnote n="227"><sup>227</sup>In mortality analysis, this is referred to as time-to-event or time-to-death.</footnote>
3. Let $\varrho$ be the discount rate and $X(t)$ a payoff function. Following the seminal paper of Yaari (1965), we define the expected present value of the payoff, taking into account the future lifetime, as:

$$ \mathbb{E}[X; t, \varrho] = \int_{t}^{\infty} e^{-\varrho(u-t)} \mathbf{S}(u|t) X(u) \, du $$

What is the rationale behind this formula?

4. The discounted remaining life expectancy is defined as the expected present value of the future lifetime:

$$ \mathrm{LE}(t; \varrho) = \mathbb{E}[1; t, \varrho] = \frac{1}{\mathbf{S}(t)} \int_{t}^{\infty} e^{-\varrho(u-t)} \mathbf{S}(u) \, du $$

Shows that:

$$ \mathrm{LE}(t; \varrho) \geq \mathrm{DLE}(t; \varrho) = \int_{t}^{\infty} e^{-\varrho(u-t)} (u-t) f(u|t) \, du $$

What is the interpretation of DLE $(t; \varrho)$? Under which condition do we have equality?

5. Assume that the survival time follows an exponential distribution: $\tau \sim \mathcal{E}(\lambda)$. Derive the formulas for $\mathrm{LE}(t; \varrho)$ and $\mathrm{DLE}(t; \varrho)$? Comment on these results.

6. We assume that life expectancy is 70 years ($\mathbb{E}[\tau] = 70$). We consider two survival functions: $\tau \sim \mathcal{E}(\lambda)$ and $\tau \sim W_{\mathrm{eibull}}(a, b)$, where the survival function is defined as $\mathbf{S}(t) = \exp\left(-\left(\frac{x}{a}\right)^b\right)$.

(a) Calibrate the parameters $\lambda$ and $a$ so that $b = 5$. Plot the survival functions $\mathbf{S}(t)$ and $\mathbf{S}(u|t = 50)$. Comment on these results.

(b) We assume that $\varrho = 3\%$. Calculate $\mathrm{LE}(0; \varrho)$ and $\mathrm{DLE}(0; \varrho)$ if the survival time is exponential.

(c) Assume that the survival time is Weibull distributed. Using numerical integration, plot the discounted life expectancy $\mathrm{LE}(t; \varrho)$ for $t \in [0, 100]$ and for different discount rates $\varrho$ (0%, 1%, 2%, 3% and 10%). Comment on these results.

7. We assume that the quality life weight $\hat{Q}(t)$ is a random variable between 0 and 1, and we note $Q(t) = \mathbb{E}[\hat{Q}(t)]$ its expected value. The quality-adjusted life expectancy (QALE) is defined as $\mathrm{QALE}(t; \varrho) = \mathbb{E}[Q(t); t, \varphi]$.

(a) Give the formula of $\mathrm{QALE}(t; \varrho)$ when the function $Q(t)$ is constant.

(b) Show that:

$$ \mathrm{QALE}(t; \varrho) \leq \mathrm{LE}(t; \varrho) $$

(c) Consider the previously calibrated Weibull distribution. We assume that:

$$ Q_1(t) = \begin{cases} 1 & \text{if } t \leq t_1 \\ 1 - \kappa_1 \frac{(t - t_1)}{t_2 - t_1} & \text{if } t_1 \leq t \leq t_2 \\ 1 - \kappa_1 - \kappa_2 \frac{(t - t_2)}{t_3 - t_2} & \text{if } t_2 \leq t \leq t_3 \\ 1 - \kappa_1 - \kappa_2 & \text{if } t \geq t_3 \end{cases} $$
What is the rationale for this specification? We consider a second HRQL function:

$$Q_2(t) = \exp(-\kappa t)$$

Compare QALE ($t; \varrho$) and LE ($t; \varrho$) for the following set of parameters: $t_1 = 50$, $\kappa_1 = 10\%$, $t_2 = 70$, $\kappa_2 = 20\%$, $t_3 = 90$, and $\kappa = 2\%$.

8. Let $\mathcal{R}(t)$ be the impact on mortality risk. We use the convention that $\mathcal{R}(t)$ is positive if the impact is a risk reduction and negative if the impact is a risk increase. We define $\Delta L(t) = \mathcal{R}(t) \cdot \Delta t$ as the expected number of lives saved (or the decrease in the number of deaths) during the short time interval $\Delta t$. Hammitt (2023) also defines the increase in life expectancy as $\Delta LE(t) = \Delta L(t) \cdot LE(t; \varrho)$ and the increase in quality-adjusted life expectancy as $\Delta QALE(t) = \Delta L(t) \cdot QALE(t; \varrho)$. The monetary value $v$ of the risk reduction $\mathcal{R}(t)$ is the product of the value of a statistical life (VSL) and the expected number of lives saved. Similarly, $v$ can be expressed as the product of the value per statistical life year (VSLY) and the increase in life expectancy or as the product of the value per quality-adjusted life year (VQALY) and the increase in quality-adjusted life expectancy. Following Hammitt (2023), we have:

$$v = \text{VSL}(t) \cdot \Delta L(t) = \text{VSLY}(t) \cdot \Delta LE(t) = \text{VQALY}(t) \cdot \Delta QALE(t)$$

(a) Find VSL ($t$) and express VSLY ($t$) and VQALY ($t$) as functions of VSL ($t$).

(b) Hammitt (2023) considers persistent risk impact $\mathcal{I}(t)$ and defines the economic gain from risk reduction as:

$$\mathcal{G}(t; \varrho) = \frac{1}{\mathbf{S}(t)} \int_{t}^{\infty} e^{-\varrho(u-t)} \mathbf{S}(u) \text{VSL}(u) \mathcal{I}(u) \, du$$

What is the interpretation of $\mathcal{G}(t; \varrho)$? Assume that $\mathcal{I}(t) = \mathcal{R}(t)$. What is the associated payoff function. Give the expression for the payoff function using VSLY ($t$) or VQALY ($t$).

(c) What is the value of $\mathcal{G}(t; \varrho)$ if VSL ($t$) and $\mathcal{I}(t)$ are assumed to be constant?

(d) In the case of air pollution, the economic cost is sometimes estimated using the following formula:

$$C = \text{VSLY} \cdot \text{YLL}$$

What is the rationale for this formula?

(e) Consider a numerical application using the previously calibrated Weibull distribution and the HRQL function $Q_1(t)$. Compute the values of LE ($t; \varrho$) and QALE ($t; \varrho$) for $t \in \{0, 40, 80\}$ and $\varrho \in \{0, 3\%\}$. Workers in an industry are paid an additional $1000 per year to face a 1 in 10000 increased risk of death. Compute the value of a statistical life. Deduce the values of VSLY ($t$) and VQALY ($t$). What is the drawback of assuming a constant VSL regardless the worker's age. Therefore, we prefer to assume a constant VSLY ($t$), equal to $150000$. Deduce the values of VSL ($t$) and VQALY ($t$). Calculate the economic gain $\mathcal{G}(t; \varrho)$ of a policy that avoids 5 deaths among 100000 people. Comment on these results.
<figure><img src="image_265.png" /></figure>
Chapter 6

Engagement & Voting Policy

According to GSIA (2021), corporate engagement & shareholder action is one of the seven categories of ESG strategies. It is defined as “employing shareholder power to influence corporate behaviour, including through direct corporate engagement (i.e., communicating with senior management and/or boards of companies), filing or co-filing shareholder proposals, and proxy voting that is guided by comprehensive ESG guidelines.” While this category of ESG strategies goes by different names — engagement and voting on sustainability matters for Eurosif, active ownership for the PRI — the scope of ESG engagement is well defined. It refers to the process of interacting with companies to encourage them to adopt sustainable and socially responsible practices. This may involve discussing issues related to corporate social responsibility and the sustainability impact of the business with company management and board members, and working with them to develop and implement practices that are aligned with the shareholder’s ESG principles. ESG engagement can be conducted by asset owners, asset managers, or organizations that seek to influence corporate behavior (e.g., Climate Action 100+). However, the ultimate goal of ESG engagement is always to align companies’ ESG practices with investors’ ESG expectations. ESG engagement is often confused with the term ESG stewardship. In fact, ESG engagement is part of ESG stewardship, but the latter is a broader concept and refers to all the actions asset owners and managers take to encourage companies to adopt sustainable and socially responsible practices. Of course, engagement is the cornerstone of stewardship because shareholder engagement and voting are the most direct ways to influence companies. However, companies are also impacted when an investor implements ESG scoring or publishes its exclusion list. Increasingly, we see the term stewardship replacing the term engagement. For instance, the publication of ESG stewardship reports by asset owners and managers has replaced the publication of ESG engagement over the past three years. In February 2021, the PRI published the guide “Stewardship” on active ownership:

> "It guides investors on how to implement the PRI's Principle 2, which sets out signatories' commitment to stewardship, stating: we will be active owners and incorporate ESG issues into our ownership policies and practices. [...] The PRI defines stewardship as the use of influence by institutional investors to maximise overall long-term value including the value of common economic, social and environmental assets, on which returns and clients' and beneficiaries' interests depend." (PRI, 2021a).

While ESG engagement and ESG stewardship are closely related concepts, ESG stewardship is gener-
ally interpreted by investors as their ESG policies, including rating models, strategies, organizations,
etc. In this chapter, in a first section, we focus on active ownership and define the different forms of
ESG shareholder activism. In a second section, we examine the voting policies of ESG investors.
# 6.1 Active ownership

## 6.1.1 Definition

From an ESG perspective, the terms active ownership, engagement and shareholder activism are interchangeable. Shareholder activism is certainly the term most often used by academics, while professionals prefer to talk about engagement and active ownership. A shareholder activist is a shareholder who uses his or her stake in a (listed) company to influence the board of directors and change the way the company is managed. For example, Gillan and Starks (2000) define active shareholders as “investors who, dissatisfied with some aspect of a company's management or operations, try to bring about change within the company without a change in control.” The changes may relate to the business model, strategy or ESG policies. Passive shareholders, on the other hand, are investors who own shares in the company but have no intention of influencing the company. When we refer to ESG engagement, the issues focus on sustainable and socially responsible practices.

Conflicts of interest between shareholders and management are well documented and central in the theory of the firm (Williamson, 1970; Jensen and Meckling, 1976). Indeed, shareholders and management may have different goals. In particular, the concept of “managerial entrenchment” refers to the tendency of managers to act in their own self-interest with a short-term time horizon rather than in the interests of shareholders, whose objective is to improve the long-term performance of the firm. In this context, managers may seek to maximize their own utility rather than the utility of shareholders, who are the owners of the firm. For example, managers have incentives to grow firms beyond optimal size because it increases their power, the resources under their control, and also their compensation (Murphy, 1985). Similarly, the separation of ownership and control, corporate social responsibility, and the definition of a corporate objective function can lead to a misalignment of preferences between shareholders and the board of directors (Jensen and Meckling, 1976). Therefore, active shareholders can serve as effective monitors of management behavior, especially when agency costs emerge<fnref n="1" /> (Jensen, 1993) or negative externalities can generate large potential costs.

The debate about the separation of ownership and control is amplified when we introduce stakeholder theory (Freeman, 2004). In fact, there may be some conflict between shareholders and stakeholders because shareholders do not necessarily have ESG preferences. On page 3, we have already mentioned the debate between the classical shareholder theory and the stakeholder theory. For Friedman (1970), “the social responsibility of business is to increase its profits.” Nevertheless, the shareholder vs. stakeholder debate has changed over time as more and more investors, especially institutional investors, have now sustainability preferences. Moreover, corporate social responsibility has evolved quite spectacularly since the seminal publication of Bowen (1953) — see for instance Drucker (1954), Jones (1980), Mintzberg (1983), Drucker (1984), Wood (1991), Mitchell et al. (1997), Carroll (1999), Crowther and Aras (2008), Carroll and Shabana (2010), Jha and Cox (2015) and Yuan et al. (2020). It is now widely accepted that corporations also have social responsibilities. Peter Drucker summarizes it as follows: “leaders in every single institution and in every single sector ... have two responsibilities. They are responsible and accountable for the performance of their institutions, and that requires them and their institutions to be concentrated, focused, limited. They are responsible also, however, for the community as a whole.” For corporations, this implies an unlimited liability clause with respect to their employees, their consumers, and society as a whole. One of the main objectives is then to minimize legal problems. This is especially true for negative

<footnote n="1">¹The main reason for this is that internal control mechanisms are generally not designed to oversee the chief executive officer and senior managers of the company. Therefore, the board of directors is the only way to supervise the CEO and his or her actions. In some cases, this supervision is reversed, i.e., the CEO supervises and controls the board of directors.</footnote>
externalities on the environment caused by the company. This echoes the liability risks defined by Carney (2015):

> "[...] the impacts that could arise tomorrow if parties who have suffered loss or damage from the effects of climate change seek compensation from those they hold responsible. Such claims could come decades in the future [...]."

The current context is very different from the 1970s, when Milton Friedman wrote his famous article. Today, corporate social responsibility is no longer an option. However, this does not mean that there is complete alignment between management, shareholders and stakeholders.

### 6.1.2 The various forms of active ownership

According to Bekjarovski and Brière (2018), active ownership can take several forms:

1. Engage behind the scenes with management and the board;

2. Propose resolutions (shareholder proposals);

3. Vote (form coalition, express dissent, call back lent shares);

4. Voice displeasure publicly (in the media);

5. Initiate a takeover (acquire a sizable equity share);

6. Exit (sell shares, take an offsetting bet, divestment);

The first two approaches take the form of dialogue between investors and companies, involving direct communication with company management and board members to discuss ESG issues. This is particularly true for the first approach. It is also the case for the second approach, as resolutions are discussed prior to annual general meetings (AGMs). The third approach can be considered one of the financial obligations of investors. This is certainly the most common way to participate in the life of a company once a year. The last three approaches take the form of an action or reaction if investors do not agree with the company's sustainability policy or the results of the AGM. We generally find all of these six approaches (except initiating a takeover) in the engagement/sustainability/stewardship reports of asset owners and managers (Figure 6.1).

**Remark 71** The first five approaches are complementary, while exit corresponds to a non-return situation. In the latter case, the engagement process between the investor and the company is terminated as the investor is no longer a shareholder of the company.

#### Engage behind the scenes

Twenty years ago, meetings between management and a company's board of directors were rare. In addition to public meetings following earnings announcements, communication between investors and investee companies typically took the form of a morning breakfast where a selection of equity or credit analysts were invited to meet with a company representative, usually the chief financial officer (CFO). This has changed over time, particularly with the development of extra-financial analysis. Today, private communication between ESG investors and companies has become very common. Engage behind the scenes refers to any meetings or actions taken by the active shareholder to better understand the ESG strategy of companies and to challenge companies on specific sustainability issues:
<table><caption>Figure 6.1: Example of engagement/sustainability/stewardship reports</caption><thead><tr><th></th><th></th><th></th></tr></thead><tbody><tr><td>J.P.Morgan AM (2021)</td><td>NBIM (2021)</td><td>Robeco (2021)</td></tr><tr><td>GSAM (2021)</td><td>BNPP AM (2021)</td><td>USS (2021)</td></tr><tr><td>Raipen (2022)</td><td>Invesco (2021)</td><td>COE (2021)</td></tr></tbody></table>

Source: Corporate websites.

> "Behind the curtain engagement involves private communication between activist shareholders and the firm's board or management, that tends to precede public measures such as vote, shareholder proposals and voice. In a sense, the existence of other forms of public activism can be taken as a signal that behind the scene engagements were unsuccessful. When it comes to environmental and social issues, writing to the board or management is a common method though which shareholders can express concern and attempt to influence corporate policy behind the curtain; alternatively, face to face meetings with management or non-executive directors are a more common behind the scene engagement method when it comes to governance." (Bekjarovski and Brière, 2018, page 10)

In fact, we can group these face-to-face meetings and more formal exchanges (letters and position statements) into three families:

1. Ongoing engagement, where the goal for investors is to explain their ESG policies and gather
information from the company. For instance, they may encourage companies to adopt ESG best practices, alert companies to ESG risks, or better understand sector-specific ESG challenges;

2. Engagement for influence (or protest), where the goal is to express dissatisfaction with respect to specific ESG issues, make recommendations to the company and measure/control companies' ESG progress;

3. Pre-AGM engagement, where the goal is to discuss with companies any resolution items that the investor may vote against.

For many years, engage behind the scenes was very informal, relying primarily on ESG analysts. This is no longer the case. Most investors now have an engagement process in place, generally based on three steps. The first step is to create an engagement list of a few issues. The idea is to focus on the most important issues, not to cover everything. Second, each engagement item is screened to identify the most serious cases. Finally, engagement can begin with the targeted companies. As noted in PRI (2019c), formalizing policies and processes is important, but the ultimate goal of active ownership is to achieve results. Therefore, investors need to track their engagement. The different stages are:

* Issues are brought to the attention of the company;

* Issues are acknowledged by the company;

* The company develops a strategy to address the issues;

* The company implements changes and the issues are resolved;

* The company does not resolve the issues and the engagement fails.

**Remark 72** *Although investors claim that transparency is the cornerstone of their stewardship and engagement practices, most of them never publish the list of companies and issues they target. Sometimes they provide anonymous examples in their engagement reports.*

It is very difficult to obtain public statistics about the engagement behind the scenes and its evolution. For instance, McCahery et al. (2016) found that “63% of the respondents state that, in the past five years, they have engaged in direct discussions with management, and 45% have had private discussions with a company's board outside of management's presence”, but these results are based on a survey of 143 respondents relative to 3 300 invitations sent between December 2012 and July 2013. More recently, the study by Barko et al. (2022) is based on a proprietary database provided by a large European asset manager. We can always find figures from stewardship and engagement reports, but it gives a partial view of this topic. For example, Amundi (French asset manager, €2 064 tn in assets under management) reports 2 334 engagements in 2021 with the following breakdown by ESG theme<fnref n="2" />: dialogue to foster a stronger voting exercise and a sounder corporate governance (1 033), transition to a low-carbon economy (547), strong governance for sustainable development (287), social cohesion through the protection of direct and indirect employees (222), preservation of natural capital (165) and product, client, societal responsibility (80). The first category corresponds to the 2021 pre-AGM dialogue statistics, which means that the Amundi corporate governance team had dialogue with 1 033 issuers in 2021. The 2 334 engagements can be broken down into 397 soft engagements, 904 active engagements, 654 voting alerts and 379 pre-AGM dialogues. Amundi also states that it engaged with 1 364 individual companies in 2021. A second example of asset managers

<footnote n="2">²Source: Amundi (2022), 2021 Engagement Report, https://about.amundi.com/esg-documentation.</footnote>
<figure><img src="image_266.png" /><figcaption>Figure 6.2: Difference between stewardship and engagement reports</figcaption></figure>

Source: Amundi corporate website, https://about.amundi.com/esg-documentation.

is Robeco, which is a Dutch asset manager with €200.7 bn in assets under management at the end of 2021. They reported 270 engagement cases<fnref n="3" /> (79 environmental issues, 76 social issues, 52 governance issues, 35 SDG issues and 28 global controversial issues), while the number of engagement activities was 942 including 393 conference calls, 402 written correspondence, and 4 physical meetings. In terms of asset owners, PGGM (Dutch pension fund with €293.5 bn in assets under management at the end of 2021) reported 154 corporate engagements in its 2021 integrated annual report<fnref n="4" />. A second example of asset owners is the Norway's sovereign wealth fund, which managed €1.24 bn at the end of 2021. They held a total of 2 628 meetings with 1 163 companies<fnref n="5" />, and they had written communications with 486 companies in 2021. They also gave the breakdown by topic<fnref n="6" />: **E** climate change (797), circular economy (190), biodiversity (48), ocean sustainability (18), etc.; **S** children's rights (40), data privacy (34), customer interests (129), etc.; **G** effective boards (267), compensation (183), shareholder protection (68), etc. These four examples concern large investors, but smaller investors also communicate about their engagement policies. Platypus Asset Management, an Australian boutique firm with $5 bn in assets under management, conducted 66 one-on-one meetings on ESG issues in 2021. Their 2021 engagement report<fnref n="7" /> is very transparent as they list the date of each meeting, the name of the company, the ESG issue, and a summary of the meeting<fnref n="8" />.

<footnote n="3">³Source: Robeco (2022), Active Ownership Report Q4 2021, www.robeco.com/en-int/sustainable-investing/influence.</footnote>

<footnote n="4">⁴Source: PGGM (2022), 2021 Integrated Annual Report, www.pggm.nl/en/integrated-report.</footnote>

<footnote n="5">⁵Source: NBIM (2022), Government Pension Fund Global 2021 — Responsible Investment, www.nbim.no/en/publications/reports/2021/responsible-investment-2021.</footnote>

<footnote n="6">⁶The total is greater than 2 628 because several topics can be discussed during a meeting.</footnote>

<footnote n="7">⁷Source: Platypus Asset Management (2022), Engagement Report 2021, www.platypusassetmanagement.com.au/~/media/platypus/documents/media/engagement-report.ashx.</footnote>

<footnote n="8">⁸For instance, on 9 June 2021, they met with FPH on general governance. Here is the summary: "*Discussed Fisher and Paykel's approach to ESG including carbon — embodied emissions, very impressive science-based reduction*</footnote>
## Propose resolutions

According to the SEC (Securities Exchange Act Rule 14a-8, §240), “a shareholder proposal or resolution is a recommendation or requirement that the company and/or its board of directors take action, which the shareholder intend to present at a meeting of the company’s shareholders. The proposal should state as clearly as possible the course of action that the shareholder believes the company should follow. If the proposal is placed on the company’s proxy card, the company must also provide in the form of proxy means for shareholders to specify by boxes a choice between approval or disapproval, or abstention.” Generally, shareholder resolutions are presented to management. Nevertheless, not all proposals submitted to management are necessarily accepted. In the US, if a company wants to exclude a shareholder proposal, it can write a letter to the SEC explaining that the proposal violates one or more conditions of SEC Rule 14a-8 (Matsusaka et al., 2021). Shareholder resolutions may be excluded because of procedural requirements<fnref n="9" /> or substantive bases<fnref n="10" />. Then, the SEC may or may not accept the exclusion. If the SEC accepts the exclusion, the company receives a “no-action” letter, indicating that the SEC will take no action if the company omits the proposal from the proxy statement<fnref n="11" />. Other countries have different rules for submitting and approving shareholder proposals. In France, Germany and the United Kingdom, shareholders can submit a resolution to the company if they own at least 5% of the capital. This threshold is 2.5% in Italy, 0.33% in the Netherlands and 3% in Spain. If shareholders organize jointly, the rule is the same in France, Germany, Italy and the Netherlands. In Spain, there is no provision for shareholders to organize jointly. In the UK, they must represent 100 shareholders and have an investment of at least £10,000.

A shareholder resolution can be seen as an escalation in the context of failed engagement or lack of responsiveness by the company. It is a way for investors to publicly demonstrate that they are not satisfied with management. However, even if the resolution is approved by a majority of shareholders, its implementation may be an issue. In the US, for instance, shareholder resolutions are not binding. This is not the case in Europe, but the management of the company can always delay implementation or consider partial implementation. In this context, shareholder resolutions are seen more as a negative signal or a dissent sent to the company and the market, especially if they receive media coverage and attention. Nevertheless, shareholder resolutions that are voted on

<footnote>targets including Scope 3, dovetails nicely with focus on product quality/need to scrutinise supply chain. The CEO is focused on emissions and potential cost impact of the transition on the business. Also discussed gender diversity and modern slavery.”</footnote>

<footnote n="9">⁹The procedural requirements are described in Rules 14a-8(b)-(h): proponent must have continuously held shares worth $2000 or 1% of the company’s value for at least one year prior submitting the proposal and must continue to hold them through the date of the meeting; proponent may submit only one proposal per meeting; proposal and supporting statement may not exceed 500 words; proposal must be submitted at least 120 days before the proxy statement is mailed; proponent or representative must be present at the meeting (Matsusaka et al., 2021, Table 1).</footnote>

<footnote n="10">¹⁰The thirteen substantive bases are described in Rule 14a-8(i): improper subject for action under state law; will cause the company to violate state, federal, or foreign law to which it is subject; proposal and supporting statement are materially false or misleading; relates to redress of a personal claim or grievance, or be designed to provide a benefit to proponent that is not shared by the other shareholders at large; relates to operations that account for less than 5 percent of company assets or sales; company lacks the power to implement; deals with ordinary business operations; would disqualify a director candidate, remove a director from office, question competence of director or nominee, seek to include specific nominee, or otherwise affect the outcome of director election; conflicts with company’s own proposal; company has already substantially implemented proposal; substantially duplicates another proposal; deals with substantially the same subject as another proposal from previous years that received (specified) low support from shareholders; relates to specific amounts of dividends (Matsusaka et al., 2021, Table 1).</footnote>

<footnote n="11">¹¹On page 3, we saw that shareholders organized resolutions against the production of napalm during the Vietnam War. For example, the Medical Committee for Human Rights filed a shareholder proposal in 1969 to force the Dow Chemical Company to stop producing napalm. The SEC allowed Dow to exclude this shareholder proposal from its 1970 proxy voting, and so the proposal was not presented to shareholders at the 1970 annual general meeting.</footnote>
are an exception. For example, below we report some figures<fnref n="12" /> for companies in the Russell 3000 Index as of proxy season 2022 (from 1st June 2021 to 30 June 2022):

* 98% of proposals are submitted by management, while less than 2% are shareholder resolutions;

* Only 60% of shareholder resolutions are voted on; the other 40% are omitted, not filed, with-drawn or pending;

* The average number of shareholder proposals per company is about two;

* Proponents of shareholder resolutions are concentrated among a small number of investors or organizations (15 proponents were responsible of 75% of shareholder proposals);

* The breakdown of shareholder proposals voted in 2022 was as follows: 11% related to E issues, 41% related to S issues and 48% related to G issues.

These figures show that there are few shareholder proposals and that they are generally submitted by the same group of investors. In fact, many shareholder proposals that are filed to proxy voting are withdrawn following negotiations between shareholders and management before the annual general meeting<fnref n="13" />. Few investors therefore have a real experience of a shareholder resolution that is voted on at the AGM.

## Vote

In just five years, voting at annual general meetings has become the norm for ESG investors. It is now considered a fiduciary duty of asset owners and managers, and evidence that an investor is socially responsible. Today, voting decisions are scrutinized and analyzed by many associations and NGOs. For instance, new editions of the Voting Matters series published by ShareAction<fnref n="14" /> are eagerly awaited by asset managers.

The voting landscape has evolved significantly in recent years, particularly in Europe. In the US, mutual funds have a long history of voting at shareholder meetings, as the SEC has always considered voting to be one of the most important fiduciary duties of mutual funds<fnref n="15" />. This explains why US mutual funds have a higher proportion of voting participation than European mutual funds. In fact, the ESG fad has changed in many different ways the activity of voting, which is now a priority from investors. First, the gap between asset owners and asset managers has has narrowed considerably, whereas the voting participation of asset managers was poor ten years ago (Brière et al., 2020). Second, voting infrastructures have been more strongly developed in Europe, while they have existed in the US for many years. Nevertheless, the proxy advisory market is dominated by

<footnote n="12">¹²We use the reports of Rosati et al. (2022) and Tonello (2022).</footnote>

<footnote n="13">¹³An example can be found in the 2021 Stewardship report of Robeco: "At the end of 2020, we filed a shareholder resolution at ADM's 2021 shareholder meeting, asking the company to step up its efforts to eliminate deforestation in its soy supply chain. After several weeks of intense negotiations, spanning across multiple meetings with ADM's head of sustainability and corporate secretary, we managed to get the company to agree to most of our key requests and so we withdrew the proposal. Our achievement was to ensure that ADM published a revised no-deforestation policy, and committed to eliminate deforestation from all its supply chains by 2030." (Robeco, 2021, page 32). ADM is a company that specializes in food, pet and animal nutrition. Other examples can be found in the stewardship reports of Amundi, Candriam, Groupama Asset Management, etc.</footnote>

<footnote n="14">¹⁴ShareAction is a UK-based registered charity that promotes responsible investment.</footnote>

<footnote n="15">¹⁵You may consult the speech "*Every Vote Counts: The Importance of Fund Voting and Disclosure*" by the Commissioner Allison Herren Lee at the 2021 ICI Mutual Funds and Investment Management Conference (March 17, 2021, www.sec.gov/news/speech/lee-every-vote-counts).</footnote>
<figure><img src="image_267.png" /><figcaption>Figure 6.3: Voting Matters series of ShareAction</figcaption></figure>

Source: https://shareaction.org.

two US proxy advisory firms<fnref n="16" /> (Institutional Shareholder Services, or ISS, and Glass Lewis), which represent 97% of the market. Third, asset managers are under great pressure to vote if they want to be credible. Voting has become a central pillar of any responsible investment policy, and it is now part of the ESG credentials that asset owners use to select asset managers.

In 2002, the United Kingdom adopted legislation requiring companies to allow shareholders to have a mandatory but non-binding vote on executive compensation at each annual general meeting. This concept is called *say on pay*. According to Rosati et al. (2022), the results for the 2022 season showed an increasing in shareholder opposition on this issue. For instance, support for executive remuneration was 87% for Russell 3000 companies in 2022 compared to 89% in 2021. Norwegian Cruise Line Holdings was the worst performer, with only 15.4% of votes for. In Europe, we see the same phenomenon. In Germany, 25% of say on pay votes were contested. In France and Spain, the most controversial resolution was the remuneration policy proposal. For example, about 50% of say on pay resolutions in France received at least 10% of shareholder opposition. For comparison, the average support rate for management proposals is generally very high, exceeding 95%.

Say on climate is inspired by say on pay proposals. This initiative<fnref n="17" /> was launched by hedge fund activist investor Chris Hohn through the Children's Investment Fund Foundation (CIFF) in 2020. It is supported by CIFF, CDP, ShareAction and the Australasian Centre for Corporate Responsibility (ACRR). More generally, a say on climate is any shareholder or management resolution on the company's climate strategy. If it is filed by the management, they expect that shareholders to vote for (shareholder approval of the climate strategy). If it is filed by shareholders, the resolution is against the company's climate strategy. In 2021, 26 companies<fnref n="18" /> presented a climate strategy at their annual general meetings<fnref n="19" /> and there were 88 climate-related shareholder proposals that were voted on (ISS Governance, 2022). The average support rate was 93% for resolutions filed by the company and 32.7% for resolutions proposed by shareholders.

<footnote n="16">¹⁶Their websites are www.issgovernance.com/solutions/proxy-voting-services and www.glasslewis.com.</footnote>

<footnote n="17">¹⁷The website is www.sayonclimate.org.</footnote>

<footnote n="18">¹⁸19 were in Europe (3 in France, 5 in Spain, 1 in Switzerland and 10 in the United Kingdom), 3 in North America (1 in Canada and 2 in the United States), 3 in South Africa and 1 in Australia.</footnote>

<footnote n="19">¹⁹In 2022, the number of companies increased and reached 36. Among them, we find seven oil and gas companies (BP, Equinor, Repsol, Santos, Shell, TotalEnergies, Woodside Petroleum).</footnote>
As we have seen, there are few shareholder proposals per company. The number of voted share-
holder proposals is even smaller. For instance, among the Russell 3000 companies, there were only
555 shareholder resolutions voted in 2022, or less than 1 resolution for 5 companies. In Figure 6.4,
we have shown the average support rate. In 2022, it is less than 40% for governance issues and
drops to 29% for environmental and social issues. Finally, the number of voted proposals received
majority support is 82. This means that there was one shareholder resolution that was approved
for 37 companies. Therefore, we can question the impact and effectiveness of voting. This explains
that voting is another form of voice for many academics.

<figure><img src="image_268.png" /><figcaption>Figure 6.4: Average support rate of shareholder proposals (Russell 3000 companies)</figcaption></figure>

Source: PwC's Governance Insights Center (2022).

Focus on the year 2022 and the US, the main topics of shareholder proposals were emissions reduction targets and Scope 3 inclusion for the E pillar; diversity, civil rights and racial equity audits, human rights and employee harassment for the S pillar; and executive compensation and political lobbying for the G pillar (Rosati et al., 2022). In Europe, most shareholder resolutions are about executive pay.

**Remark 73** The voting behavior of asset managers is analyzed in Section 6.2.4 on page 597.

Voice

The term voice was popularized in 1970 by economist Albert Hirschman, when he published his book “*Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States*”. The book states that members of an organization have two main possible responses when they believe the organization is failing. They can exit (withdraw from the relationship) or they can voice (change the relationship by communicating the complaint). From a socio-economic perspective, exit is associated
<figure><img src="image_269.png" /><figcaption>Figure 6.5: Pass rate of shareholder proposals (Russell 3000 companies)</figcaption></figure>

Source: Tonello (2022).

with Adam Smith's invisible hand, while voice is inherently political and can be confrontational. The exit-voice model of Hirschman (1970) can be applied to many situations: protest movements, migration, class actions, and even corporate governance (Kostant, 1999).

In the theory of shareholder activism, voice can refer to different forms of engagement, such as engage behind the scenes or propose resolutions (Edmans, 2014). In this chapter, voice refers to a situation in which the communication between activist shareholders and the company becomes public. Like resolution proposals, voice can be interpreted as a form of escalation. Indeed, the debate and the disagreement become public, which means that other stakeholders are informed and can participate, such as other shareholders, the media, politics and society. The company then faces the risk of being placed in the political spotlight and having to respond to public criticism and scrutiny. The situation can become uncomfortable for the company, especially if non-technical stakeholders (the media and society) focus on the issue.

According to McCahery et al. (2016), voice is rarely used by individual institutional investors. One reason is that public communication may be ineffective, justifying the prevalence of behind the scenes communication (Levit, 2019). However, the use of voice has increased in recent years due to two main factors. The first is that collaborative engagement between investors is now quite common, thanks to initiatives such as the PRI or Climate Action 100+. In this context, they require more transparency by tracking the progress of each member. For example, when signing up to the Climate Action 100+ initiative, investors are asked to nominate which focus companies they wish to engage with, and whether this is as a lead investor or a collaborating investor. The second factor is the increasing involvement of NGOs in the debate on engagement and greenwashing<fnref n="20" />. In this

<footnote n="20">²⁰For instance, we can cite the following examples among others: As You Sow, Citizens' Climate Lobby, Climate</footnote>
context, investors sometimes have to answer publicly to greenwashing suspicions or accusations for supporting and financing some companies that are considered by these NGOs to be harmful to the environment or human health. All these elements explain why the voice against companies, but also the voice against investors, has recently gained in importance.

## Initiate a takeover

Acquiring a large stake in a company is an aggressive form of shareholder activism. The underlying idea is to form a coalition with other large shareholders to obtain a board set and ultimately control the company's board. This strategy is typically implemented by activist hedge funds (Gantchev, 2013). In general, managers perceive activist events as a hostile act because their compensation and job security are threatened (Gantchev et al., 2019). In most cases, this form of shareholder activism has a great impact on the company (change of business strategy, implementation of proposed solutions, etc.). However, it has never been used by ESG investors. Therefore, it is only motivated by financial underperformance and not by extra-financial issues.

## Exit

Exit refers to the process of selling investments in a particular company or industry. Divestment is a more general term that implies a significant reduction in exposure. In this case, we refer to a partial divestment, while an exit corresponds to a full divestment<fnref n="21" />. For example, investors may decide to divest from a company if they are not satisfied with its ESG performance, particularly if the company's policies implicate social issues or if it does not take sufficient action to address environmental concerns. Investors may also decide to divest from a sector such as fossil fuels or tobacco. The exit policy is therefore linked to two ESG investment strategies: exclusion and norms-based screening<fnref n="22" />. Nevertheless, divestment cannot be equated with these ESG strategies. In fact, the concept of divestment/exit implies that investors are currently invested in the company and decide to sell their participation because they disagree with the company's ESG policies. In this context, divestment is the ultimate engagement action, meaning that investors believe they cannot influence the company's behavior by staying invested. In this case, divestment is "*the final step in an escalation strategy*" (PRI, 2022a) and can be seen as a failure of engagement on the part of investors. When it concerns an industry, divestment may be motivated by high risks or low opportunities for the industry to transition to a more sustainable business model. For example, divestment from coal reserves or the mining sector can reduce the investors' exposure to the risk of stranded assets<fnref n="23" />. As we saw in the first chapter, exit can also be motivated by moral values. In this case, it is consistent with the norms-based screening strategy.

The case of the fossil fuel sector is certainly the most symbolic divestment issue. According to the Global Divestment Commitments Database, approximately 1600 institutions<fnref n="24" /> have committed to divest from fossil fuels as of January 2024. In Figure 6.6, we show the breakdown by type of organization. The top three categories are faith-based organizations, educational institutions, and philanthropic foundations, representing 63.50% of divesting institutions. They are followed by pension funds. Commitments fall into four categories: (1) thermal coal only, (2) coal and tar sands, (3) partial divestment from some but not all types of fossil fuel companies, (4) full divestment from

<footnote>Alliance, Friends of the Earth, Fund Our Future, Oxfam, Reclaim Finance and Sunrise Movement.</footnote>

<footnote n="21">²¹Nevertheless, we note that the two terms are often used interchangeably.</footnote>

<footnote n="22">²²These strategies are described on page 44.</footnote>

<footnote n="23">²³Stranded assets are discussed in Section 10.3 on page 1009.</footnote>

<footnote n="24">²⁴Including Axa Insurance, La Banque Postale, Harvard University, the State of Maine, the Norwegian Sovereign Wealth Fund, and the University of Oxford.</footnote>
Box 6.1: Case study: the Cambridge University endowment fund

In their research paper “To Divest or to Engage? A Case Study of Investor Responses to Climate Activism”, Chambers et al. (2020) examined the interesting case of the Cambridge University endowment fund:

> "A dilemma faced by an increasing number of investors is whether to divest from environmentally damaging businesses or whether to enter into a dialogue with them. This predicament now has its epicentre in Cambridge, England, where the ancient University of Cambridge faces great pressure from students and staff to respond to the threat of climate breakdown. Having already received two reports on its approach to responsible investment, the university has appointed a new chief investment officer (CIO) who, alongside University Council and the wider university community, needs to consider the question of whether to divest from or to engage with fossil-fuel firms."

This paper tells the story of the Cambridge fossil fuel divestment movement from 2012 to 2020. This includes the creation of the Positive Investment Cambridge group, the establishment of the Ethical Investment Working Group, the publication of several reports, many Zero Carbon Society petitions in favor of fossil fuel divestment, the formation of the Divestment Working Group, the activism of students and faculty staff, the involvement of many distinguished scholars, including prestigious professors (e.g., astronomer Royal officer, Nobel laureate, chief scientific adviser, distinguished statisticians, Fields medalists, fellows of the Royal Academy and the Royal Society), etc. The research paper shows how the pressure on institutional investors to respond to climate activism can be accelerated. It concludes that "investment professionals need to understand the forces for change", "a head-in-the-sand response is counter-productive" and "changes in investment policy should be evidence-based."

any fossil fuel company (thermal coal, oil, gas). Some investors are already “fossil free”, meaning that they currently have no investments in fossil fuel companies and are committed to avoiding any fossil fuel investments in the future. The debate about fossil fuel divestment is tough, because it is not only an investor debate, but also a societal one. In Box 6.1, we report on the tense relationship between the two sides. We find that the decision to divest or not can be motivated by considerations other than rational evidence. Pressure from anti-fossil fuel movements may be one factor, fear of greenwashing another. Moreover, “exit relaxes the tension between the activist and the board” (Levit, 2019). In some ways, exit is a comfortable position. The investor can continue to communicate with the company, but the situation is completely different. Before the exit, the investor has to convince the company to move. After the exit, the company has to prove that it will change and convince the investor to come back. So the roles are reversed.

We have already seen that vote is a form of voice. For Admati and Pfleiderer (2009), exit is also a form of voice. Most academic studies show that the effects of exit are mixed because the costs of divestment can be high and its effectiveness is limited (Jahnke, 2019; Levit, 2019; Broccardo et al., 2022; Edmans et al., 2022). For some academics, the impact of divestment may also be negative:

> "Large divestment campaigns are undertaken in part to depress share prices of firms that investors see as engaged in harmful activities. We show that, if successful, investors who divest earn lower and riskier returns than those that do not, leading them to control
<figure><img src="image_270.png" /><figcaption>Figure 6.6: What kinds of institutions are divesting from fossil fuel?</figcaption></figure>

Source: https://divestmentdatabase.org.

> a decreasing share of wealth over time. Divestment therefore has only a temporary price impact. Further, we show that, for standard managerial compensation schemes, divestment campaigns actually provide an incentive for executives to increase, not reduce, the harm that they create. Therefore, divestment is both counter-productive in the short run, and self-defeating in the long run.” (Davies and Van Wesep, 2018, page 558).

In fact, we need to distinguish between the effects on the primary and secondary markets. In theory, divestment reduces the price of the company's shares on the secondary market, which means that expected returns increase. On the primary market, it leads to a higher cost of capital due to lower demand. Thus, the rationale for exit is the effect on the cost of capital. However, it is difficult to verify this effect empirically over the last 10 years. Academics are more unanimous when they examine the effect before exit. In fact, according to Edmans (2009), the threat of exit has more impact than divestment itself, and “*the power of loyalty relies on the threat of exit.*” Again, we see that voice and exit are complementary rather than mutually exclusive.

### 6.1.3 Individual versus collective engagement

Coordinating engagement efforts between different asset owners and managers can lead to several key benefits and increase efficiency compared to individual engagement (Gillan and Starks, 2000). The doctrine was established in 2018 by PRI (2018a, pages 16 and 17). According to this research, investors tend to prefer to engage with companies on ESG issues on an individual basis, as this allows for a more tailored approach to meet each investor's unique requirements. However, investors and companies also identified a potential downside to this approach in terms of cost and duplication of requests, particularly when multiple investors make similar requests. For example, during a controversy, investor demands may suddenly increase and become difficult for the company to manage.
Box 6.2: Case studies of fossil fuel divestment

Church of England Pensions Board

By the end of 2021, the CoE Pensions Board was responsible for nearly £3.7 bn of assets across three pension schemes. In July 2018, the General Synod of the Church of England voted on a motion to ensure that by 2023 CoE pension funds will have divested from fossil fuel companies that are not prepared to align with the goals of the Paris Agreement. In 2020, they engaged with 21 companies. At the end of the process, 12 companies were deemed to be making sufficient progress, while 9 companies were added to the list of restricted investments. These divestments totaled £32.23 mn.

Source: Church of England Pensions Board, Stewardship Report 2020.

The Universities Superannuation Scheme (USS)

The Universities Superannuation Scheme (USS) is the pension scheme for university staff in the UK. It manages about £90 bn. In 2020, USS undertook a review of the sectors in which the scheme invests. They concluded that, in several cases, the outcomes predicted by the market did not adequately take into account the potential financial impact of certain specific risks, including ESG. As a result, they excluded certain sectors: tobacco manufacturing; thermal coal mining (coal to be burned for electricity generation), specifically where they accounted for more than 25% of revenues; and certain controversial weapons. The first exclusion was announced in May 2020. Divestment from these sectors was completed two years later. According to Ethics for USS (a group of USS members committed to reforming USS and ensuring an investment strategy that protects the planet, respects human rights, invests responsibly, and provides good pensions), “USS still has large investments in the industries responsible for the climate emergency [...], while they recognise that USS has made plans to decarbonize its investment portfolio.” Ethics for USS estimates that “USS continues to invest £570 mn in 48 leading fossil fuels companies”, and USS should expand its divestment policy “to include other companies that have not committed to a credible path towards zero emissions.”

Source: USS, Stewardship Code Report 2022 & https://divestuss.org.

In Table 6.1, we report the pros and cons of individual and collective forms of engagement. For investors, the advantages of collective engagement are:

* By combining their resources and voices, investors can put more pressure on companies to address their concerns.

* A unified stance from diverse investors sends a clear and consistent message to companies, creating a stronger signal.

* Collaboration saves time and resources for all participants and enhances the credibility of the engagement process.

However, collective engagement can be negative if investors are not aligned and investors have different requirements. It is therefore important that collective engagement is managed by a lead investor. We have seen that the two most prominent coordinated engagement initiatives are those of PRI and Climate Action 100+, but other notable initiatives include the Ceres Investor Network, the Institutional Investors Group on Climate Change (IIGCC), and the Net Zero Asset Managers initiative
(NZAM). Using a database of engagements provided by PRI, Dimson et al. (2021) discuss globally coordinated engagements by long-term shareholders to influence companies on environmental and social issues. It highlights a two-tier strategy involving lead and supporting investors as effective, leading to improved target performance and increased fund flows. Factors influencing leadership include higher stakes, geographic and cultural proximity, and the domestic presence of lead investors. The study also emphasizes the growing prevalence of these engagements, driven by institutional expertise and interest, and concludes that structured engagement strategies help achieve goals.

<table><caption>Table 6.1: Pros and cons of individual and collective forms of engagement</caption><thead><tr><th rowspan="2"></th><th colspan="2">INDIVIDUAL INVESTOR ESG ENGAGEMENTS</th><th colspan="2">COLLECTIVE INVESTOR ESG ENGAGEMENTS</th></tr><tr><th>Corporate Perceptions</th><th>Investor Perceptions</th><th>Corporate Perceptions</th><th>Investor Perceptions</th></tr></thead><tbody><tr><td>PROS</td><td><ul><li>Face-to-face and one-to-one dialogues are effective to address multiple ESG issues.</li><li>Avoidance of misrepresentation of ESG performance by third-parties.</li><li>One-to-one interactions allow the building of trust, and long-term relationships, with investors.</li></ul></td><td><ul><li>Alignment of engagement goals with internal ESG and engagement policies.</li><li>Strategic benefits of proactively addressing emerging ESG topics.</li><li>Enables a strategic focus on corporate stocks with ambiguous ESG scores.</li></ul></td><td><ul><li>Larger, collective assets under management working together can give more leverage to internal corporate drives on ESG issues.</li><li>Cost savings in terms of time spent with investors.</li><li>Perceived higher ESG expertise of the investor group.</li></ul></td><td><ul><li>Higher power and influence through the collective assets under management.</li><li>More relevant for systemic and marketplace issues, or if investors have 'thematic' engagement policies.</li><li>Cost savings on monitoring.</li></ul></td></tr><tr><td>CONS</td><td><ul><li>Need to manage numerous, different investor requests.</li><li>Redundancy in questions asked by multiple, individual investors.</li><li>Costly and time consuming process, especially if ESG requests by multiple investors increase.</li></ul></td><td><ul><li>Potentially low shareholding insufficient to capture board-level attention.</li><li>Limited resources that can be spent to maintain the continuity of engagement and/or financial analyst engagement.</li></ul></td><td><ul><li>Lack of interest from investors for overall corporate ESG management activities, due to specific ESG thematic focus.</li><li>Higher coordination costs if investors fail to coordinate their efforts.</li><li>Investors with no or too little shareholding may attend meetings.</li></ul></td><td><ul><li>Broad international focus that may not be coherent with national investment strategies.</li><li>Possibility of free-riding.</li><li>Time-consuming process if investor views are divergent.</li></ul></td></tr></tbody></table>

Source: PRI (2018a, Table 3).

### 6.1.4 The role of institutional investors

The impact of institutional investors<fnref n="25" /> on corporate governance has been extensively studied by academics (Gillan and Starks, 2000; Appel et al., 2016; Chen et al., 2020). One of their conclusions is that the role of these investors in companies is growing. One reason is that institutional ownership has increased over time for two reasons. They manage more money than they used to, and they have

<footnote n="25">²⁵Institutional investors include asset owners (endowments, insurance companies, pension funds, sovereign wealth funds) and asset managers (ETFs, hedge funds, mutual funds).</footnote>
increased their allocation to equity markets. An history of institutional shareholder activism can be found in Gillan and Starks (2000). However, institutional active ownership has been accelerated by the issue of climate change (Krueger et al., 2020), and the definition of fiduciary duty is at the heart of this issue. This is especially true for pension funds. Even the ETF industry has been affected by the active ownership phenomenon. In particular, we can cite the article of Appel et al. (2016): Passive Investors, Not Passive Owners<fnref n="26" />. Today, we can say that engagement has become a pillar of the investment process for these institutional investors.

To illustrate the importance of institutional investors, we look at several examples. Below, we list Apple's top 5 institutional investors based on the company's 2023 annual report<fnref n="27" />:

<table><thead><tr><td>#</td><td>Investor</td><td>Stock outstanding</td></tr></thead><tbody><tr><td>1</td><td>Vanguard</td><td>8.36%</td></tr><tr><td>2</td><td>Blackrock</td><td>6.30%</td></tr><tr><td>3</td><td>Berkshire Hathaway</td><td>5.80%</td></tr><tr><td>4</td><td>State Street</td><td>3.66%</td></tr><tr><td>5</td><td>Fidelity Investments</td><td>1.90%</td></tr></tbody></table>

According to www.techopedia.com, “Apple’s initial institutional shareholders are not clearly documented, but by delving into the company’s proxy filings from 1994, we can gain some insight. As of November 30, 1994, the only institutional shareholder listed was the Capital Group. This company [...] held a significant stake in Apple at that time. Their holdings amounted to 11.84 million shares, which constituted 9.8% of Apple’s total outstanding stock. By 2010, Blackrock and Fidelity Investment had become key Apple shareholders, with Blackrock holding 5.50% and Fidelity 5.04% of the total stock. However, by late 2015, Vanguard Group emerged as Apple’s largest shareholder [...] Berkshire Hathaway became one of Apple’s biggest shareholders in 2020.” In general, we can find the shareholding structure of companies in their annual reports. Thus, in 2023, institutional investors own 83% of General Electric, 78% of Danone and Sanofi, 77% of Goldman Sachs, 75% of Total, 70% of McDonald, 65% of Coca-Cola, 58% of Ford Motor Company and 51% of ENI. This ratio depends very much on the history of the company, as some companies may be mainly owned by the founder, a government, a family or private investors. For instance, 43% of Tesla is owned by private investors, including Elon Musk, who is Tesla’s largest individual shareholder with a 12.93% stake. LVMH’s capital structure is dominated by the Arnaud family group (48.2%), followed by foreign institutional investors (38.2%) and French institutional investors (7.3%).

According to Medina et al. (2022), institutional investors<fnref n="28" /> account for approximately 43% of global market capitalization in 2020 followed by the corporations (11%), the public sector (10%) and strategic individuals (9%). Other free-float investors include direct retail investors, corporations and institutional investors whose holdings are below the disclosure thresholds. They represent 27% of global market capitalization. However, these global figures mask a wide variation across countries. The share of institutional investors varies from a negligible percentage in Bulgaria, Lithuania and Saudi Arabia to more than 60% in Iceland, the United Kingdom and the United States (Table 6.2). The total holdings of the 50 largest institutional investors in the stock market increased by 80% between 2007 and 2019. In 2020, they represented 27% of the equity market capitalization. If we look at companies in investable indexes, institutional ownership is even larger. In fact, institutional

<footnote n="26">²⁶The study concludes that “passive mutual funds influence firms’ governance choices, resulting in more independent directors, removal of takeover defenses, and more equal voting rights.”</footnote>

<footnote n="27">²⁷Source: www.techopedia.com/largest-apple-shareholder.</footnote>

<footnote n="28">²⁸The following percentages are underestimated as they only include institutional investors whose holdings are public because they are above the disclosure thresholds.</footnote>
<table><caption>Table 6.2: Ownership by investor category as share of market capitalisation (in %, December 2020)</caption><thead><tr><th rowspan="2">Country</th><th rowspan="2">Corporation</th><th rowspan="2">Public sector</th><th rowspan="2">Strategic individual</th><th rowspan="2">Institutional</th><th rowspan="2">Other free-float</th><th colspan="2">Non-domestic</th></tr><tr><th>Total</th><th>% Instit.</th></tr></thead><tbody><tr><td>Argentina</td><td>25</td><td>17</td><td>17</td><td>10</td><td>31</td><td>10</td><td>42</td></tr><tr><td>Australia</td><td>5</td><td>2</td><td>6</td><td>27</td><td>60</td><td>16</td><td>80</td></tr><tr><td>Austria</td><td>21</td><td>23</td><td>6</td><td>23</td><td>27</td><td>15</td><td>56</td></tr><tr><td>Belgium</td><td>26</td><td>3</td><td>7</td><td>35</td><td>29</td><td>33</td><td>70</td></tr><tr><td>Brazil</td><td>29</td><td>10</td><td>8</td><td>27</td><td>26</td><td>17</td><td>57</td></tr><tr><td>Bulgaria</td><td>75</td><td>2</td><td>9</td><td>1</td><td>13</td><td>0</td><td>0</td></tr><tr><td>Canada</td><td>6</td><td>4</td><td>4</td><td>46</td><td>40</td><td>23</td><td>88</td></tr><tr><td>Chile</td><td>54</td><td>1</td><td>13</td><td>12</td><td>20</td><td>6</td><td>24</td></tr><tr><td>China</td><td>12</td><td>29</td><td>18</td><td>11</td><td>30</td><td>3</td><td>50</td></tr><tr><td>Colombia</td><td>32</td><td>35</td><td>3</td><td>16</td><td>14</td><td>6</td><td>43</td></tr><tr><td>Croatia</td><td>57</td><td>17</td><td>5</td><td>10</td><td>11</td><td>1</td><td>2</td></tr><tr><td>Denmark</td><td>10</td><td>10</td><td>2</td><td>36</td><td>42</td><td>27</td><td>93</td></tr><tr><td>Estonia</td><td>35</td><td>17</td><td>14</td><td>11</td><td>23</td><td>7</td><td>58</td></tr><tr><td>Finland</td><td>5</td><td>17</td><td>9</td><td>31</td><td>38</td><td>21</td><td>88</td></tr><tr><td>France</td><td>20</td><td>6</td><td>14</td><td>27</td><td>33</td><td>21</td><td>70</td></tr><tr><td>Germany</td><td>15</td><td>7</td><td>10</td><td>30</td><td>38</td><td>23</td><td>72</td></tr><tr><td>Greece</td><td>25</td><td>11</td><td>14</td><td>16</td><td>34</td><td>14</td><td>44</td></tr><tr><td>Hong Kong</td><td>22</td><td>11</td><td>19</td><td>18</td><td>30</td><td>15</td><td>27</td></tr><tr><td>Hungary</td><td>21</td><td>5</td><td>6</td><td>32</td><td>36</td><td>26</td><td>74</td></tr><tr><td>Iceland</td><td>9</td><td>1</td><td>7</td><td>66</td><td>17</td><td>16</td><td>94</td></tr><tr><td>India</td><td>33</td><td>12</td><td>11</td><td>22</td><td>22</td><td>13</td><td>57</td></tr><tr><td>Indonesia</td><td>43</td><td>17</td><td>10</td><td>8</td><td>22</td><td>8</td><td>30</td></tr><tr><td>Ireland</td><td>6</td><td>8</td><td>4</td><td>49</td><td>33</td><td>48</td><td>92</td></tr><tr><td>Israel</td><td>19</td><td>1</td><td>19</td><td>31</td><td>30</td><td>14</td><td>74</td></tr><tr><td>Italy</td><td>13</td><td>11</td><td>11</td><td>29</td><td>36</td><td>25</td><td>81</td></tr><tr><td>Japan</td><td>22</td><td>3</td><td>6</td><td>30</td><td>39</td><td>15</td><td>79</td></tr><tr><td>Korea</td><td>23</td><td>10</td><td>10</td><td>18</td><td>39</td><td>15</td><td>83</td></tr><tr><td>Lithuania</td><td>27</td><td>43</td><td>10</td><td>2</td><td>18</td><td>2</td><td>6</td></tr><tr><td>Mexico</td><td>19</td><td>2</td><td>34</td><td>20</td><td>25</td><td>13</td><td>45</td></tr><tr><td>Netherlands</td><td>20</td><td>3</td><td>4</td><td>40</td><td>33</td><td>37</td><td>67</td></tr><tr><td>New Zealand</td><td>6</td><td>19</td><td>5</td><td>20</td><td>50</td><td>16</td><td>84</td></tr><tr><td>Norway</td><td>10</td><td>29</td><td>9</td><td>30</td><td>22</td><td>18</td><td>72</td></tr><tr><td>Poland</td><td>17</td><td>14</td><td>14</td><td>35</td><td>20</td><td>19</td><td>53</td></tr><tr><td>Portugal</td><td>37</td><td>13</td><td>10</td><td>22</td><td>18</td><td>21</td><td>54</td></tr><tr><td>Romania</td><td>30</td><td>28</td><td>2</td><td>16</td><td>24</td><td>7</td><td>21</td></tr><tr><td>Russia</td><td>18</td><td>31</td><td>17</td><td>11</td><td>23</td><td>10</td><td>45</td></tr><tr><td>Saudi Arabia</td><td>2</td><td>87</td><td>2</td><td>1</td><td>8</td><td>1</td><td>50</td></tr><tr><td>Slovenia</td><td>14</td><td>34</td><td>0</td><td>8</td><td>44</td><td>7</td><td>47</td></tr><tr><td>South Africa</td><td>20</td><td>15</td><td>3</td><td>31</td><td>31</td><td>19</td><td>56</td></tr><tr><td>Spain</td><td>13</td><td>7</td><td>16</td><td>25</td><td>39</td><td>24</td><td>67</td></tr><tr><td>Sweden</td><td>12</td><td>6</td><td>12</td><td>38</td><td>32</td><td>19</td><td>79</td></tr><tr><td>Switzerland</td><td>6</td><td>6</td><td>6</td><td>33</td><td>49</td><td>26</td><td>84</td></tr><tr><td>Turkey</td><td>38</td><td>25</td><td>9</td><td>9</td><td>19</td><td>5</td><td>15</td></tr><tr><td>United Kingdom</td><td>6</td><td>6</td><td>4</td><td>60</td><td>24</td><td>32</td><td>76</td></tr><tr><td>United States</td><td>3</td><td>3</td><td>6</td><td>68</td><td>20</td><td>11</td><td>69</td></tr></tbody><tfoot><tr><td>Total</td><td>11</td><td>10</td><td>9</td><td>43</td><td>27</td><td></td><td></td></tr></tfoot></table>

Source: Medina et al. (2022, Table A.1, page 47).