# Lecture Notes on Biodiversity

Thierry Roncalli

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Distributed under a Creative Commons Attribution 4.0 International License
Lecture Notes
On Biodiversity

Thierry Roncalli

Université Paris-Saclay
Copyright © 2025 by Thierry Roncalli

<figure><img src="image_2.png" /></figure>

This book is published under a CC BY license (Creative Commons Attribution 4.0 International License)

https://creativecommons.org/licenses/by/4.0

This version: March 7, 2025.
# Table of Contents

## Introduction 8

## 1 Definition 9

### 1.1 Key components of biodiversity 9

#### 1.1.1 Genetic diversity 10

#### 1.1.2 Species diversity 13

#### 1.1.3 Ecological diversity 16

### 1.2 Biodiversity loss (and gain) 17

#### 1.2.1 Speciation, extinction and the birth-death model 18

#### 1.2.2 Background extension rate 22

#### 1.2.3 Mass extinction 23

#### 1.2.4 The Holocene extinction, the Anthropocene extinction or the sixth mass extinction? 27

### 1.3 Biodiversity hotspot 36

## 2 Ecosystem functions and services 37

### 2.1 Definition 37

### 2.2 Natural capital 39

### 2.3 Pollination service 45

### 2.4 Food and feed service 55

#### 2.4.1 Food production 55

#### 2.4.2 Food consumption 58

#### 2.4.3 Food security 60

## 3 Biodiversity threats and risks 71

### 3.1 Habitat loss, fragmentation and degradation 75

#### 3.1.1 Theory of island biogeography 76

#### 3.1.2 Species-area relationship 77

#### 3.1.3 Species distribution, sampling and endemics-area curve 82

#### 3.1.4 Forest loss 98

### 3.2 Invasive species 106

### 3.3 Pollution 110

#### 3.3.1 Types of biodiversity pollution 110

#### 3.3.2 Dose-response relationship 120

#### 3.3.3 Application to air quality standards 124

#### 3.3.4 Air quality index 126

#### 3.3.5 The cost of pollution 129

### 3.4 Overexploitation and resource extraction 145

#### 3.4.1 An example with freshwater 148

#### 3.4.2 Mathematical models of population and resource ecology with harvesting 151

#### 3.4.3 Overexploitation in aquatic systems 167

#### 3.4.4 Overexploitation in tropical forests 176

### 3.5 Climate change 182
<table><tbody><tr><td><strong>4 Biodiversity measurement</strong></td><td><strong>182</strong></td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;4.1 Essential biodiversity variables</td><td>182</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;4.2 Biodiversity metrics</td><td>184</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;4.2.1 Mean species abundance (MSA)</td><td>184</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;4.2.2 Potentially disappeared fraction (PDF)</td><td>186</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;4.2.3 Biodiversity intactness index (BII)</td><td>187</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;4.2.4 Species threat abatement and restoration (STAR)</td><td>188</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;4.2.5 Comparison of these methodologies</td><td>189</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;4.3 Commercial solutions</td><td>190</td></tr><tr><td><strong>5 Biodiversity governance and regulation</strong></td><td><strong>192</strong></td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;5.1 Convention on Biodiversity (CBD)</td><td>192</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;5.1.1 Aichi Biodiversity Targets</td><td>193</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;5.1.2 Kunming-Montreal Global Biodiversity Framework</td><td>194</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;5.2 IPBES</td><td>198</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;5.3 TNFD</td><td>199</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;5.4 European biodiversity framework</td><td>200</td></tr><tr><td><strong>6 Investment approaches</strong></td><td><strong>202</strong></td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;6.1 Financial instruments</td><td>202</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;6.2 The avoid-minimize-restore-offset approach</td><td>204</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;6.3 The impact investing approach</td><td>206</td></tr><tr><td><strong>Bibliography</strong></td><td><strong>208</strong></td></tr><tr><td><strong>A Exercises</strong></td><td><strong>230</strong></td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;A.1 Calculating the prevalence of undernourishment</td><td>230</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;A.2 Calculating the species-area relationship using the theory of island biogeography</td><td>232</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;A.3 Species abundance models</td><td>234</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;A.4 Valuation of risks to life and health</td><td>235</td></tr><tr><td><strong>B Solutions to the Tutorial Exercises</strong></td><td><strong>238</strong></td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;B.1 Calculating the prevalence of undernourishment</td><td>238</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;B.2 Calculating the species-area relationship using the theory of island biogeography</td><td>245</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;B.3 Species abundance models</td><td>255</td></tr><tr><td>&nbsp;&nbsp;&nbsp;&nbsp;B.4 Valuation of risks to life and health</td><td>260</td></tr></tbody></table>
Abbreviations

AQI Air quality index.

BII Biodiversity intactness index.

BMI Body mass index.

CBD Convention on biological diversity.

CICES Common international classification of ecosystem services.

CITES Convention on international trade in endangered species of wild fauna and flora.

COP Conference of the parties.

CRF Concentration-response function.

CSR Corporate social responsibility.

DALY Disability-adjusted life years.

DEC Dietary energy consumption.

DNSH Do no significant harm.

EAR Endemics-area relationship.

EEA European environment agency.

ENCORE Exploring natural capital opportunities, risks and exposure.

EPA Environmental protection agency.

ESG Environmental, social and governance.

FAO Food and agriculture organization.

FSB Financial stability board.

GBF Kunming-Montreal global biodiversity framework.

GMO Genetically modified organism.

IAS Invasive alien species.

IASB International accounting standards board.

IBAT Integrated Biodiversity Assessment Tool.

IEA International energy agency.

IFRS International financial reporting standards.

IPBES Intergovernmental science-policy platform on biodiversity and ecosystem services.

IPCC Intergovernmental panel on climate change.

ISSB International sustainability A standards board.

IUCN International union for conservation of nature.

LCA Life cycle assessment.

LPI Living planet index.

LULUCF Land use, land-use change, and forestry.

MDER Minimum dietary energy requirement.

MSA Mean species abundance.

MSY Maximum sustainable yield.

NCAVES Natural capital accounting and valuation of ecosystem services.

NGFS Network of central banks and supervisors for greening the financial system.

NGO Non-governmental organization.

OECD Organisation for economic cooperation and development.

OPS One planet summit.

PDF Potentially disappeared fraction.

PM Particulate matter.

POP Persistent organic pollutant.

PRI Principles for responsible investment.

QALE Quality-adjusted life expectancy.

QALY Quality-adjusted life year.

RLI Red list index.

SAC Species accumulation curve.

SAD Species abundance distribution.

SAR Species-area relationship.

SDG Sustainable development goal.

SEEA System of environmental-economic accounting.

STAR Species Threat Abatement and Restoration metric.

TCFD Task force on climate-related financial disclosures.

TEEB The economics of ecosystems and biodiversity.

TIB Theory of island biogeography.

TNFD Task force on nature-related financial disclosures.

UNDP United Nations development programme.

UNEP United Nations environment programme.
**UNEP FI** United Nations environment programme finance initiative.

**UNFCCC** UN framework convention on climate change.

**VOLY** Value of life year.

**VSL** Value of a statistical life.

**VSLY** Value per statistical life year.

**WDPA** World Database on Protected Areas.

**WEF** World economic forum.

**WHO** World health organization.

**WRI** World resources institute.

**YLD** Years lived with disability.

**YLL** Years of life lost.
Abstract

These lecture notes are part of the Handbook of Sustainable Finance (Roncalli, 2025). They provide the basics of biodiversity for students and professionals who want to understand this topic and the key challenges of biodiversity investing. The first three sections cover the definition of biodiversity, ecosystem functions and services, and threats to biodiversity. These correspond to material typically taught in conservation biology courses. The fourth section focuses on measuring biodiversity. Finally, the last two sections cover biodiversity governance and regulation, and biodiversity investment approaches.

In these lecture notes, we will learn that biodiversity goes far beyond the issues of species ex-
tinction and deforestation. In fact, it is much broader and includes fisheries, food security, health
issues, invasive species, natural resources, pollution, and water stress, among others. However, most
measures of biodiversity focus primarily on species richness, abundance, or extinction. From a finan-
cial perspective, this is unsatisfactory, and biodiversity finance requires more sophisticated metrics.
In addition, new regulations and frameworks are pushing investors to become actively involved in
biodiversity restoration. The concept of double materiality also underscores the importance of bio-
diversity to companies and implies some hidden risks in financial assets because they impact or
can be impacted by biodiversity loss. Despite growing awareness, long-term investors are not yet
fully equipped to integrate biodiversity risks into their investment decisions. While progress is being
made, there is still a long way to go in developing robust methodologies that can effectively integrate
biodiversity into sustainable investment strategies.

**Keywords:** Biodiversity, species, ecosystem, natural capital, pollination, food security, habitat degradation, invasive species, pollution, overexploitation, biodiversity measurement, Convention on Biodiversity, TNFD, mitigation hierarchy.

JEL Classification: Q, O1, I1, G11.

Acknowledgement

I am very grateful to Wassim Le Lann of the Naturalis Biodiversity Center (Netherlands) for his
helpful comments, the various discussions we had about biodiversity, and the materials he provided.
**Introduction**

Biodiversity has become an important issue in the ESG financial community in recent years. For example, the SFDR's mandatory principal adverse impact indicator on biodiversity (PAI 7) requires companies to disclose activities that negatively impact biodiversity sensitive areas<fnref n="1" />, the sixth economic objective of the EU green taxonomy is the protection and restoration of biodiversity and ecosystems<fnref n="2" /> while the ESRS E4 category of the CSRD is named biodiversity and ecosystems<fnref n="3" />. In this context, where biodiversity is an important issue in sustainable finance regulations, it was obvious that investors wanted to develop biodiversity products or manage investments with respect to biodiversity risks and they have done so. And this is certainly just the beginning. When we talk about biodiversity, the two words that come to mind are risk and impact. It's easy to take the shortcut that an investment that takes biodiversity into account is an investment with impact, but does that mean it falls into the category of impact investing? Generally not, because there is a significant difference between investing in assets that carry biodiversity risks and investing with the goal of having a positive impact on biodiversity. To understand this distinction between investing with impact and investing for impact, it is important to first define what biodiversity really means<fnref n="4" />.

<figure><img src="image_3.png" /><figcaption>Box 1: Edward O. Wilson</figcaption></figure>

<footnote n="1">¹See Roncalli (2025, Section 1.4.3, page 36 & Table 1.8, 38).</footnote>

<footnote n="2">²See Roncalli (2025, Section 1.4.1, page 33).</footnote>

<footnote n="3">³See Roncalli (2025, Section 1.4.5, page 39).</footnote>

<footnote n="4">⁴This section is based on the textbook *Biodiversity: An Introduction* written by Kevin Gaston and John Spicer and the scientific book *Conservation Biology for All* edited by Navjot Sodhi and Paul Ehrlich. *Essentials of Conservation Biology* by Richard Primack is another reference book, but it is more advanced and technical.</footnote>
# 1 Definition

Biodiversity, or biological diversity, refers to the variety and variability of life on Earth in all its many manifestations. According to Gaston and Spicer (2004), it is a broad, unifying concept that encompasses all forms, levels, and combinations of natural variation at all levels of biological organization. For example, it includes genetic diversity within species, the diversity of species in different habitats, and the diversity of ecosystems themselves. In other words, biodiversity encompasses all living organisms, from the smallest bacteria to the largest mammals, and the complex relationships and interactions among them. In addition, biodiversity is essential to the health of ecosystems, providing critical services such as air and water purification, crop pollination, climate regulation and food production.

**Remark 1** In the scientific world, biodiversity is generally associated with conservation biology, the scientific discipline dedicated to understanding and preserving biodiversity and protecting ecosystems. This field emerged in response to the rapid loss of biodiversity due to human activities such as habitat destruction, pollution, and climate change. Biodiversity and conservation biology are therefore closely related, which is why many master's programs use both the term biodiversity and conservation biology.

## 1.1 Key components of biodiversity

There are several ways to assess and measure biodiversity. In general, we consider three building blocks:

1. Genetic diversity

This refers to the variety of genes within a species, such as different varieties of rice. Genetic diversity is essential for the survival and adaptability of species, allowing them to evolve in response to changing conditions.

2. Organismal (or species) diversity

This refers to the variety of species in a given area or ecosystem. It includes the number of different species (species richness), the relative abundance of each species (species evenness), and variation in the distribution of species in space (beta diversity or species density). A greater number of species indicates greater biodiversity and generally contributes to more resilient ecosystems that are able to maintain their functionality after environmental changes.

3. Ecological (or ecosystem) diversity

This refers to the variety of ecosystems in a region, including different habitats, biological communities, and ecological processes. Ecosystem diversity includes forests, grasslands, wetlands, deserts, marine environments, etc. This element is essential for maintaining the range of ecological processes that support life, such as nutrient cycling, energy flow, and climate regulation.

In Table 2 we reproduce the different elements of the three building blocks, which are organized in nested hierarchies with higher and lower order elements (Gaston, 2010, pages 27-32). Some elements are specific to a given building block, e.g., nucleotides belong to the genetic diversity cluster, while other elements may be shared by two or three building blocks, e.g., individuals belong to both the genetic diversity and species diversity clusters. In addition to these three building blocks, we can consider other dimensions of biodiversity, such as functional diversity<fnref n="5" /> or temporal diversity<fnref n="6" />.

<footnote n="5">⁵Functional diversity refers to the range of different functions or roles that species play within an ecosystem.</footnote>

<footnote n="6">⁶Temporal diversity refers to changes in biodiversity over time, including seasonal variations, successional changes in ecosystems, and long-term evolutionary processes.</footnote>
<table><caption>Table 1: Elements of biodiversity</caption><thead><tr><th>Ecological diversity</th><th>Genetic diversity</th><th>Organismal diversity</th></tr></thead><tbody><tr><td>Biogeographic realms</td><td></td><td>Domains or Kingdoms</td></tr><tr><td>Biomes</td><td></td><td>Phyla</td></tr><tr><td>Provinces</td><td></td><td>Families</td></tr><tr><td>Ecoregions</td><td></td><td>Genera</td></tr><tr><td>Ecosystems</td><td></td><td>Species</td></tr><tr><td>Habitats</td><td></td><td>Subspecies</td></tr><tr><td>Populations</td><td>Populations</td><td>Populations</td></tr><tr><td></td><td>Individuals</td><td>Individuals</td></tr><tr><td></td><td>Chromosomes</td><td></td></tr><tr><td></td><td>Genes</td><td></td></tr><tr><td></td><td>Nucleotides</td><td></td></tr></tbody></table>

Source: Heywood (1995) & Gaston (2010, Table 2.1, page 27).

### 1.1.1 Genetic diversity

Genetic (or genomic) diversity can be assessed at different structural levels: nucleotides, genes, or chromosomes. Thus, we can measure genetic diversity by nucleotide<fnref n="7" /> differences, allelic diversity (average number of alleles per locus), gene diversity or polymorphism (proportion of polymorphic loci<fnref n="8" /> across the genome), and heterozygosity<fnref n="9" />.

<figure><img src="image_4.png" /><figcaption>Figure 1: Nucleotides, genes, and chromosomes</figcaption></figure>

Source: blog.myheritage.com/2018/02/dna-basics-chapter-3-dna-expression.

<footnote n="7">⁷For example, adenine (A), cytosine (C), guanine (G), and thymine (T) are the four types of nucleotides that make up DNA.</footnote>

<footnote n="8">⁸At a polymorphic locus, two or more different alleles exist within a population. For example, the ABO blood group system is determined by a polymorphic locus on chromosome 9, where multiple alleles (A, B, and O) exist, resulting in different blood types. The four basic ABO phenotypes are A, B, AB, and O.</footnote>

<footnote n="9">⁹If an individual has two identical alleles at a given locus, they are said to be homozygous for that gene. If they have two different alleles, they are heterozygous.</footnote>
Box 2: Ploidy and the number of chromosomes

Ploidy is the number of sets of chromosomes in the nucleus of a cell. Ploidy varies from species to species and can even vary within the same species. A haploid cell has only one set of chromosomes, while cells with two, three, four, etc. complete sets of chromosomes are called diploid, triploid, tetraploid, and so on. The haploid number of chromosomes is called *n*, while 2*n* and *kn* are the diploid and k-ploid numbers of chromosomes, respectively. For example, humans are diploid because human cells contain two copies of each chromosome. Since humans have two copies of 23 chromosomes, the haploid number of chromosomes is *n* = 23, while the diploid number of chromosomes is 2*n* = 46. The total number of chromosomes is *kn*, where *k* is the ploidy of the cell. In the case of humans, the total number of chromosomes is then 46. Most organisms on Earth are diploid, so the reported number of chromosomes is generally the diploid number. There are some exceptions. For example, Mycoplasma, Escherichia coli (E. coli), and most bacteria are haploid organisms. Human gametes (sperm in males and egg in females) are also haploid because they are reproductive cells that contain half the number of chromosomes. This means that the number of chromosomes in the sperm or egg is *n* = 23, not 2*n* = 46. In honey bees, the diploid queen has 32 chromosomes (2*n* = 32). The drones (male bees) are entirely derived from the queen (they are formed from unfertilized eggs), which means that the haploid drones have 16 chromosomes (*n* = 16). Female worker bees, on the other hand, are derived from the mother and a father, so they are diploid organisms with 32 chromosomes (2*n* = 32). A common example of a polyploid organism is the potato:

> "Common cultivated potato varieties include tetraploid (4*n* = 48) with a basic chromosome number of 12, while there are cultivated species at the diploid (2*n* = 24) to pentaploid (5*n* = 60) levels. The triploid and pentaploid cultivated species are grown only on highland plateaus and slopes of the Andes, but diploid cultivated species are grown more widely and also used for breeding tetraploid varieties." (Watanabe, 2015, page 53).

To measure genetic diversity, we can look at the number of genes. However, we must be careful because genes can be divided into several categories based on their functions. For example, we generally distinguish between protein-coding genes, which encode instructions for the synthesis of proteins; non-coding genes, which produce RNA molecules that do not encode proteins but play an essential role in regulating gene expression and cellular processes; and pseudogenes, which are inactive copies of protein-coding genes. A more complex measure is genome size, also called C-value. The C-value is the amount of DNA contained in a haploid set of chromosomes. It is typically measured in picograms (pg) or base pairs (bp). A base pair is the basic unit of DNA sequence and corresponds to two nucleotides that combine to form the DNA double helix. The conversion between C-value and base pairs uses the following correspondence: 1 picogram is equal to 978 Mbp (million base pairs). For example, Gaston (2010, page 28) reports that the genome size of eukaryotic organisms (animals, plants, fungi, and many unicellular organisms) varies enormously, with C-values ranging from 0.0023 pg (or 2.25 million base pairs) for the parasitic microsporidium *Encephalitozoon intestinalis* to 1 400 pg (or 1.369 trillion base pairs) for the free-living amoeba *Chaos chaos*.

For a given organism, the number of genes and the C-value may vary from one measurement to another. They depend on the sample, the measurement instrument, the data size, etc. Therefore, most numbers are revised over time as data collection becomes more complete. Consider the human
genome. Twenty years ago, Taft and Mattick (2003) wrote: "Until recently, the estimated number of protein-coding genes in the human genome was predicted to range from as low as 40 000 to as high as 120 000. However, it is now apparent that humans have no more than 30 000 protein-coding genes, similar to other vertebrates such as the mouse and pufferfish". An important step in the sequencing of the human genome was taken in 2001 with the publication *The Sequence of the Human Genome* by Venter et al. (2001) in Science. They estimated 2.91 billion base pairs and 26 588 protein-coding genes. Since 2001, we have made great progress in sequencing the human genome, and the most recent published papers converge on some common numbers. Nurk et al. (2022) performed a new sequencing of the human genome and compared it to the previous reference studies performed by Schneider et al. (2017). Here are the results:

<table><thead><tr><th>Statistics</th><th>GRCH38</th><th>T2T-CHM13</th></tr></thead><tbody><tr><td>Base pairs (Gbp)</td><td>2.92</td><td>3.05</td></tr><tr><td>Number of genes</td><td>60 090</td><td>63 494</td></tr><tr><td>Number of protein-coding genes</td><td>19 890</td><td>19 969</td></tr><tr><td>% of repeats</td><td>51.89</td><td>53.94</td></tr></tbody></table>

where GRCH38 is the genomic database used by Schneider et al. (2017) and T2T-CHM13 is the genomic database used by Nurk et al. (2022). We can conclude that the human genome has 3 billion base pairs and the number of genes is 20 000. For many other organisms, the uncertainty in the number of base pairs and genes is more important because there are not enough resources (human and capital) to sequence their genomes with sophisticated instruments. Therefore, we may prefer to use the third metric of genetic diversity, the number of chromosomes, which is a more stable measure. For example, humans have exactly 46 chromosomes<fnref n="10" />, while a mouse has exactly 40 chromosomes.

<table><caption>Table 2: Genetic diversity of some organisms</caption><thead><tr><th>Organism</th><th>C-value (in pg)</th><th>Base pairs (in Mbp)</th><th>Genes (×10<sup>3</sup>)</th><th>Chromosomes (2n or kn)</th></tr></thead><tbody><tr><td>Mycoplasma (bacterium)</td><td></td><td>0.580</td><td>0.45 – 0.70</td><td>1*</td></tr><tr><td>Haemophilus influenzae (bacterium)</td><td></td><td>1.8</td><td>1.750</td><td>1*</td></tr><tr><td>Escherichia coli (bacterium)</td><td></td><td>4.6</td><td>4 – 5</td><td>1*</td></tr><tr><td>Drosophila melanogaster (fruit fly)</td><td>0.17</td><td>180</td><td>13 – 17</td><td>8</td></tr><tr><td>Arabidopsis thaliana (mustard plant)</td><td>0.14</td><td>135</td><td>27</td><td>10</td></tr><tr><td>Caenorhabditis elegans (nematode)</td><td>0.10</td><td>100</td><td>21</td><td>12</td></tr><tr><td>Saccharomyces cerevisiae (yeast)</td><td>0.02</td><td>12</td><td>6</td><td>16</td></tr><tr><td>Zea mays (corn)</td><td>2.30</td><td>2 300</td><td>32 – 40</td><td>20</td></tr><tr><td>Oryza sativa (rice)</td><td>0.40</td><td>430</td><td>32 – 50</td><td>24</td></tr><tr><td>Musmusculus (mouse)</td><td>2.60</td><td>2 700</td><td>20 – 25</td><td>40</td></tr><tr><td>Rattus norvegicus (brown rat)</td><td>2.75</td><td>2 700</td><td>20 – 25</td><td>42</td></tr><tr><td>Homo sapiens (human)</td><td>3.20</td><td>3 050</td><td>20</td><td>46</td></tr><tr><td>Solanum tuberosum (tetraploid potato)</td><td>3.50</td><td>3 400</td><td>39 – 45</td><td>48*</td></tr><tr><td>Fragaria ananassa (octoploid strawberry)</td><td>2.50</td><td>2 500</td><td>35 – 45</td><td>56*</td></tr><tr><td>Canis lupus familiaris (dog)</td><td>2.80</td><td>2 800</td><td>20</td><td>78</td></tr><tr><td>Agrodiaetus shahrami (butterfly)</td><td>0.75</td><td>750</td><td>12 – 14</td><td>100 – 268*</td></tr><tr><td>Ophioglossum reticulatum (polyploid fern)</td><td>6.25</td><td>6 200</td><td>30 – 50</td><td>1 440*</td></tr></tbody></table>

Source: Author's research.

<footnote n="10">¹⁰This is not always true. Some humans have 47 chromosomes (trisomy), while others have 45 chromosomes (monosomy).</footnote>
Table 2 shows the genetic diversity of some organisms. The first column gives the scientific name of the organism and indicates the family. Then we have the C-value calculated in pg, the genome size expressed in million base pairs, and the number of (protein-coding) genes. The last column is the number of chromosomes. The symbol * indicates that the cells are not diploid. The fern *Ophioglossum reticulatum* is the organism with the highest number of chromosomes. Interestingly, the number of chromosomes in butterflies can vary greatly from species to species. Most butterfly species have between 28 and 100 chromosomes. For example, common butterflies such as the Monarch (*Danaus plexippus*) have 30 chromosomes. Some species may have as few as 20 chromosomes or as many as 268 chromosomes, such as some *Agrodiaetus* butterflies.

<figure><img src="image_5.png" /><figcaption>Figure 2: Blue Morpho butterfly</figcaption></figure>

Source: www.color-meanings.com/colorful-butterflies.

1.1.2 Species diversity

Organismal diversity can be assessed at different levels, but the most common is species diversity. Individuals represent the first level. They are grouped into populations, which form the second level of organismal diversity. Individuals and populations are also the two last levels of genetic diversity. Finally, populations are grouped into species. Defining a species is not straightforward (De Queiroz, 2007). In common language, species refer to a group of organisms that share certain physical or morphological characteristics. For example, we might say that butterflies form a species. However, this is not true from a biological standpoint. According to *Nature*<fnref n="11" />, “*a biological species is a group of organisms that can reproduce with one another in nature and produce fertile offspring. Species are defined by the fact that they are reproductively isolated from other groups, meaning that organisms within one species cannot successfully reproduce with those of another species.*” For example, butterflies belong to families, not species. Some well-known butterfly species include the Monarch (*Danaus plexippus*) and the Blue Morpho (*Morpho menelaus*). Phylogenetics is another widely used approach to classifying organisms into species. A phylogenetic species is defined as the smallest group of organisms that share a common ancestor and can be distinguished by unique genetic or physical characteristics. Species are then grouped into genera (singular: genus), genera are assembled into families, families into phyla, and so on, progressing through higher taxonomic levels. The principal ranks in modern biological taxonomies are domain, kingdom, phylum (or division), class, order, family, genus, and species. For example, humans are classified as *Homo sapiens*, a

<footnote n="11">¹¹Source: https://www.nature.com/scitable/definition/species-312.</footnote>
species within the genus *Homo*. The *Homo* genus includes *Homo sapiens* (the only surviving species today) and several extinct species, such as *Homo neanderthalensis*, *Homo erectus*, and *Homo habilis*. *Homo* belongs to the *Hominidae* family, also known as the great apes. This family also includes chimpanzees, bonobos, and gorillas. Humans are further classified into the *Primates* order, the *Mammalia* class, the *Chordata* phylum, the *Animalia* kingdom, and the *Eukarya* domain. Readers can explore the species taxonomic tree on specialized websites<fnref n="12" />.

In 1988, Robert May published a landmark article in *Science: How Many Species are There on Earth?* This article does not answer the question in the title. Why not? Because he didn't have enough information at the time to make a confident estimate. May (1988) preferred to review the different kinds of information scientists need to produce an answer that isn't just a guess. Thirty-five years later, can we give an accurate answer? In fact, not as many scientific articles suggest:

> "In 2010, Robert May pointed out an embarrassing truth about modern science<fnref n="13" />. Even as we invest huge amounts of time, money, and effort to find life on other planets, we still do not know how much life (i.e., how many species) is on our own. Although 'do not know' might sound like hyperbole, estimates have ranged wildly, from 2 million to 3 trillion." (Wiens, 2023, page 1).

The current reference paper on this topic is Mora et al. (2011), who estimated 8.7 million (±1.3 million standard error) eukaryotic species worldwide, of which 2.2 million (±0.18 million SE) are marine. The decomposition of their estimates is shown in Table 3. This result contrasts with the 1.5 or 2 million of species catalogued in current databases, suggesting that many species remain to be discovered. However, these figures continue to be challenged by new research, most of which puts the number of species on Earth at around 11 million, not excluding the possibility that there are at least one billion species on Earth (Larsen et al., 2017).

<table><caption>Table 3: Currently catalogued and predicted total number of species on Earth and in the ocean</caption><thead><tr><th rowspan="2">Species</th><th colspan="3">Earth</th><th colspan="3">Ocean</th></tr><tr><th>Catalogued</th><th>Predicted</th><th>± SE</th><th>Catalogued</th><th>Predicted</th><th>± SE</th></tr></thead><tbody><tr><td>Eukaryotes</td><td>1 233 500</td><td>8 740 000</td><td>1 300 000</td><td>193 756</td><td>2 210 000</td><td>182 000</td></tr><tr><td>Animalia</td><td>953 434</td><td>7 770 000</td><td>958 000</td><td>171 082</td><td>2 150 000</td><td>145 000</td></tr><tr><td>Chromista</td><td>13 033</td><td>27 500</td><td>30 500</td><td>4 859</td><td>7 400</td><td>9 640</td></tr><tr><td>Fungi</td><td>43 271</td><td>611 000</td><td>297 000</td><td>1 097</td><td>5 320</td><td>11 100</td></tr><tr><td>Plantae</td><td>215 644</td><td>298 000</td><td>8 200</td><td>8 600</td><td>16 600</td><td>9 130</td></tr><tr><td>Protozoa</td><td>8 118</td><td>36 400</td><td>6 690</td><td>8 118</td><td>36 400</td><td>6 690</td></tr><tr><td>Prokaryotes</td><td>10 860</td><td>10 100</td><td>3 630</td><td>653</td><td>1 320</td><td>436</td></tr><tr><td>Archaea</td><td>502</td><td>455</td><td>160</td><td>1</td><td>1</td><td>0</td></tr><tr><td>Bacteria</td><td>10 358</td><td>9 680</td><td>3 470</td><td>652</td><td>1 320</td><td>436</td></tr></tbody><tfoot><tr><td>Total</td><td>1 244 360</td><td>8 750 000</td><td>1 300 000</td><td>194 409</td><td>2 210 000</td><td>182 000</td></tr></tfoot></table>

Source: Mora et al. (2011, Table 2, page 5).

<footnote n="12">¹²The two most popular are www.ncbi.nlm.nih.gov/taxonomy, developed by the NCBI (National Center for Biotechnology Information), and www.fws.gov/explore-taxonomic-tree, provided by the FWS (US Fish & Wildlife Service).</footnote>

<footnote n="13">¹³Here is the abstract of Robert May's paper:</footnote>

<footnote>> "If some alien version of the Starship Enterprise visited Earth, what might be the visitors' first question? I think it would be: How many distinct life forms — species — does your planet have? Embarrassingly, our best-guess answer would be in the range of 5 to 10 million eukaryotes (never mind the viruses and bacteria), but we could defend numbers exceeding 100 million, or as low as 3 million." (May, 2010, page 41).</footnote>
<table><caption>Table 4: Exploring the taxonomy classification tree</caption><thead><tr><th>Kingdom</th><th>Phylum</th><th>Class</th><th>Order</th><th>Family</th><th>Genus</th><th>Species</th><th>Vernacular name</th></tr></thead><tbody><tr><td rowspan="10">Animalia</td><td>34</td><td>109</td><td>704</td><td>10 119</td><td>164 366</td><td>1 551 595</td><td>Animals</td></tr><tr><td>Arthropoda</td><td>Insecta</td><td>43</td><td>1 738</td><td>89 273</td><td>994 767</td><td>Insects</td></tr><tr><td>Arthropoda</td><td>Insecta</td><td>Lepidoptera</td><td>Nymphalidae</td><td>Morpho</td><td>Morpho menelaus</td><td>Blue morphos</td></tr><tr><td>Chordata</td><td>Mammalia</td><td>Carnivora</td><td>Phocidae</td><td>14</td><td>19</td><td>True seals</td></tr><tr><td>Chordata</td><td>Mammalia</td><td>Carnivora</td><td>Phocidae</td><td>Phoca</td><td>Phoca largha</td><td>Large seals</td></tr><tr><td>Chordata</td><td>Mammalia</td><td>Carnivora</td><td>Phocidae</td><td>Phoca</td><td>Phoca vitulina</td><td>Common seals</td></tr><tr><td>Chordata</td><td>Mammalia</td><td>Primates</td><td>16</td><td>83</td><td>528</td><td>Primates</td></tr><tr><td>Chordata</td><td>Mammalia</td><td>Primates</td><td>Hominidae</td><td>Homo</td><td>Homo sapiens</td><td>Humans</td></tr><tr><td>Mollusca</td><td>Gastropoda</td><td>Stylommatophora</td><td>Helicidae</td><td>Helix</td><td>Helix pomatia</td><td>Escargots</td></tr><tr><td rowspan="5">Archaea</td><td>2</td><td>13</td><td>16</td><td>27</td><td>112</td><td>377</td><td></td></tr><tr><td>Crenarchaeota</td><td>Thermoprotei</td><td>Thermoproteales</td><td>Thermoproteaceae</td><td>Caldivirga</td><td>Caldivirga maquilingensis</td><td>Bacteria</td></tr><tr><td>29</td><td>51</td><td>115</td><td>297</td><td>1 996</td><td>9 980</td><td>B. anthracis</td></tr><tr><td>Pseudomonadota</td><td>Bacilli</td><td>Bacillales</td><td>Enterobacteriales</td><td>Enterobacteriaceae</td><td>7 248</td><td>61 900</td><td>E. coli</td></tr><tr><td>Chromista</td><td>Foraminifera</td><td>58</td><td>200</td><td>1 101</td><td>4 016</td><td>49 654</td><td></td></tr><tr><td rowspan="3">Fungi</td><td>12</td><td>61</td><td>274</td><td>1 086</td><td>12 778</td><td>155 869</td><td></td></tr><tr><td>Basidiomycota</td><td>Agaricomycetes</td><td>23</td><td>148</td><td>1 875</td><td>40 825</td><td></td></tr><tr><td>Basidiomycota</td><td>Agaricomycetes</td><td>Agaricales</td><td>Amanitaceae</td><td>Amanita</td><td>Amanita phalloides</td><td>Death caps</td></tr><tr><td rowspan="10">Plantae</td><td>Basidiomycota</td><td>Agaricomycetes</td><td>Boletales</td><td>Boletaceae</td><td>Boletus</td><td>Boletus edulis</td><td>Ceps</td></tr><tr><td>9</td><td>44</td><td>256</td><td>1 079</td><td>21 463</td><td>385 774</td><td>Plants</td></tr><tr><td>Tracheophyta</td><td>Liliopsida</td><td>Liliales</td><td>Liliaceae</td><td>Tulipa L.</td><td>96</td><td>Tulips</td></tr><tr><td>Tracheophyta</td><td>Magnoliopsida</td><td>Fabales</td><td>Fabaceae</td><td>Phaseolus</td><td>Phaseolus vulgaris</td><td>Common bean</td></tr><tr><td>Tracheophyta</td><td>Magnoliopsida</td><td>Rosales</td><td>Rosaceae</td><td>110</td><td>8 147</td><td>Roses</td></tr><tr><td>Tracheophyta</td><td>Magnoliopsida</td><td>Solanales</td><td>Solanaceae</td><td>102</td><td>2 808</td><td></td></tr><tr><td>Tracheophyta</td><td>Magnoliopsida</td><td>Solanales</td><td>Solanaceae</td><td>Capsicum</td><td>Capsicum annuum</td><td>Pimientos</td></tr><tr><td>Tracheophyta</td><td>Magnoliopsida</td><td>Solanales</td><td>Solanaceae</td><td>Solanum</td><td>Solanum lycopersicum</td><td>Tomatos</td></tr><tr><td>Tracheophyta</td><td>Magnoliopsida</td><td>Solanales</td><td>Solanaceae</td><td>Solanum</td><td>Solanum tuberosum</td><td>Potatos</td></tr><tr><td>Protozoa</td><td>10</td><td>41</td><td>74</td><td>227</td><td>1 090</td><td>2 659</td><td>Protozoans</td></tr><tr><td>Choanozoa</td><td>Ichthyosporea</td><td>Eccrina</td><td>Amoebidiidae</td><td>Amoebidium</td><td>Amoebidium parasiticum</td><td></td></tr></tbody></table>

For each taxon, we indicate the parent nodes of the tree on the left and the number of taxa on the right. For example, *Insecta* belongs to the phylum *Arthropoda* in the kingdom *Animalia* and includes 43 orders, 1 738 families, 89 273 genera, and 994 767 species.
### 1.1.3 Ecological diversity

The third element of biodiversity is ecosystems. Again, there are several levels of ecological diversity. Populations, which are also part of genetic and organismal diversity, are the first level. Populations are grouped into habitats. The other three levels are ecosystems, ecoregions, and provinces. Then we find the biomes, which are large-scale ecosystems characterized by similar climatic conditions, vegetation, and wildlife. We generally distinguish between terrestrial and aquatic biomes. Terrestrial biomes include boreal forests (taiga), chaparral (Mediterranean climate), deserts, savannas, temperate forests, temperate grasslands, tropical rainforests, and tundra. Aquatic biomes include freshwater biomes such as wetlands and marine biomes such as oceans, coral reefs and mangroves. The highest level of ecological diversity corresponds to biogeographic realms, which are the broadest divisions of the Earth's land surface delineated by natural barriers such as oceans, deserts, and mountain ranges. Olson et al. (2001) defined eight realms: Australasia, Antarctic, Afrotropic, Indo-Malaya, Nearctic, Neotropic, Oceania and Palearctic.

<figure><img src="image_6.png" /><figcaption>Figure 3: The 867 terrestrial ecoregions of Olson et al. (2001)</figcaption></figure>

Source: Olson et al. (2001, Figure 2, page 935).

In general, ecoregions are the most common level at which ecological diversity is assessed. The World Wide Fund for Nature (WWF) describes them as biogeographic units, which are “defined as relatively large units of land or water containing a distinct assemblage of natural communities sharing a large majority of species, dynamics, and environmental conditions.” Most current world ecoregion maps<fnref n="14" /> are based on the seminal work of Olson et al. (2001), who defined 867 distinct ecoregions (Figure 3). Among these ecosystems, Olson and Dinerstein (2002) identified 238 priority ecoregions for protection (142 terrestrial, 53 freshwater, and 43 marine). This research has been used extensively by the WWF and the International Union for Conservation of Nature (IUCN) to define protected areas<fnref n="15" />. The 2001 study was recently updated by Dinerstein et al. (2017), which

<footnote n="14">¹⁴See, for example, the maps available at https://ecoregions.appspot.com and https://www.oneearth.org/bioregions.</footnote>

<footnote n="15">¹⁵IUCN has developed a system of protected area management categories to define, record and classify the wide variety of specific goals and concerns in categorizing protected areas and their objectives. The six categories are: strict nature reserve and wilderness area (Cat. I), national park (Cat. II), natural monument or feature (Cat. III),</footnote>
now has a list of 846 terrestrial ecoregions. A more recent study used a different mapping approach and identified 431 global ecosystems (Sayre et al., 2020). By conducting a global gap analysis of the representation of these ecosystems in protected areas, the authors showed that most natural and semi-natural ecosystems are inadequately protected, with protection rates of less than 20%.

## 1.2 Biodiversity loss (and gain)

Regardless of the element of biodiversity (genetic, organismal or ecological), most figures show that the loss of biodiversity is significant and has accelerated over the past 50 years. However, such a message is not really clear. Indeed, we can first ask ourselves what biodiversity loss is, how it is measured, and is the current figure really significant? For example, the second chapter of Gaston and Spicer (2004) is devoted to the temporal dynamics of biodiversity and illustrates that biodiversity has fluctuated over geological time scales, such as millions of years. This long-term perspective shows that changes in biodiversity are a natural part of Earth's history and makes it difficult to understand whether current trends represent an exceptional crisis or a continuation of these natural cycles.

<figure><img src="image_7.png" /><figcaption>Figure 4: Genus diversity during the Phanerozoic era</figcaption></figure>

Source: Rohde and Muller (2005, Figure 1, page 208) & Supplementary Tables (www.nature.com/articles/nature03339).

The evolution of biodiversity over time is typically represented by a Sepkoski curve, which plots the number of genera over time. Although this is a simple metric, it is difficult to calculate due to

<footnote>habitat or species management area (Cat. IV), protected landscape or seascape (Cat. V), and protected area with sustainable use of natural resources (Cat. VI). For example, in France, Les Landes de Gascogne is managed under IUCN category VI of protected areas, while Le Parc du Mercantour is managed under IUCN category II. Readers can explore protected areas and other effective area-based conservation measures (OECMs) at www.protectedplanet.net.</footnote>
the complexity of data collection. Joseph John Sepkoski devoted much of his career to building a database of marine animal families and genera. This dataset, used extensively in numerous publications, was released in 2002 after Sepkoski's death (Sepkoski, 2002). Figure 4 shows the Sepkoski curve generated by Rohde and Muller (2005). The three series shown are: the total number of known genera of marine animals from Sepkoski's catalog<fnref n="16" />, the total number of well-defined genera (i.e., known genera excluding those with single occurrences or poorly dated records), and the long-term trend estimated using a third-order polynomial fitted to the data. First, we observe that the number of genera has fluctuated continuously throughout the Phanerozoic. About 500 million years ago, the number of genera was estimated at 370 000, while today it exceeds 5 million. Second, the increase in the number of genera was not linear. Genus diversity increased about 400 million years ago, then declined until about 200 million years ago, after which it increased dramatically. In the present era, genus diversity is higher than at any time in Earth's history. Finally, while the long-term trend is clear, there are numerous discontinuities with a frequency of about one million years. In particular, we observe several sharp declines known as extinction events or mass extinctions.

### 1.2.1 Speciation, extinction and the birth-death model

The number of species on Earth results from a balance between two evolutionary processes: speciation (the formation of new species) and extinction<fnref n="17" />. When speciation rates exceed extinction rates, the number of species increases. Conversely, when extinction rates exceed speciation rates, the number of species decreases. Both processes can occur naturally or be influenced by external factors. In fact, the processes of birth and death apply not only to individuals and populations, but also to higher levels of biological classification, such as species. For example, *Homo sapiens* appeared about 300 000 years ago, while *Australopithecus* disappeared about 1.9 million years ago. Similarly, dinosaurs became extinct about 65 million years ago, illustrating that species extinction is a natural process that can occur without human intervention. Thus, we generally recognize that each species and subspecies has a finite lifespan:

> "Like all species, plants, mammals, and birds have been subject to extinction as a fundamental part of evolution. Indeed, only about 2-4% of all the species that have ever lived during the 600 million years of the fossil record still survive today. Looking at the fossil record, it can be said that invertebrate species and mammals have had an average life span of 5-10 and 1-2 million years, respectively." (Mace, 1998).

Even as some species disappear, new species continue to appear. This process of species formation is called speciation or diversification (Gaston and Spicer, 2004, Section 2.3.2, page 31). Speciation most often occurs when populations of the same species become geographically isolated. Over time, these populations evolve independently, accumulating genetic changes that can eventually lead to the emergence of distinct species. As these genetic differences increase, individuals from the two populations may no longer be able to interbreed or produce fertile offspring. A classic example of this phenomenon is donkeys and horses. Both belong to the same family (*Equidae*) and genus (*Equus*), but are classified as separate species. Donkeys (*Equus africanus asinus*) are a subspecies of the African wild ass (*Equus africanus*), while domestic horses (*Equus ferus caballus*) are a subspecies of the wild horse (*Equus ferus*). Although donkeys and horses can interbreed, their offspring are usually sterile<fnref n="18" />, meaning they cannot reproduce. This sterility occurs because donkeys have 62

<footnote n="16">¹⁶The Sepkoski database can be found at https://strata.geology.wisc.edu/jack.</footnote>

<footnote n="17">¹⁷Extinction refers to the complete disappearance of a species from the Earth, while extirpation refers to the disappearance of a species from a particular region, but the species continues to exist in other regions.</footnote>

<footnote n="18">¹⁸The offspring of a female horse and a male donkey is a mule, while the offspring of a male horse and a female donkey is a hinny.</footnote>
<figure><img src="image_8.png" /><figcaption>Figure 5: Rates of origination and extinction during the Phanerozoic era</figcaption></figure>

Source: Rohde and Muller (2005) & Author's calculations.

<figure><img src="image_9.png" /><figcaption>Figure 6: Net diversification rate during the Phanerozoic era</figcaption></figure>

Source: Rohde and Muller (2005) & Author's calculations.
chromosomes while horses have 64, resulting in offspring with 63 chromosomes. In fact, donkeys, horses and zebras share a common ancestor, but diverged for various reasons. According to Carbone et al. (2006), zebras and donkeys split about 0.9 million years ago, while their common ancestor diverged from the horse about 2 million years ago.

The number of species $N(t)$ at time $t+1$ can be expressed as:

$$N(t+1) = N(t) + \Delta N^{+}(t+1) - \Delta N^{-}(t+1)$$

where $\Delta N^{+}(t+1)$ and $\Delta N^{-}(t+1)$ are the number of new species and extinct species between $t$ and $t+1$. In continuous time, this equation becomes:

$$\frac{dN(t)}{dt} = \frac{dN^{+}(t)}{dt} - \frac{dN^{-}(t)}{dt}$$

Dividing both sides by $N(t)$ gives:

$$\underbrace{\frac{dN(t)}{N(t) dt}}_{\delta(t)} = \underbrace{\frac{dN^{+}(t)}{N(t) dt}}_{\lambda(t)} - \underbrace{\frac{dN^{-}(t)}{N(t) dt}}_{\mu(t)}$$

The growth rate $\delta(t)$ is the difference between the origination (or speciation) rate $\lambda(t)$ and the extinction rate $\mu(t)$:

$$\delta(t) = \lambda(t) - \mu(t) \qquad (1)$$

$\delta(t)$ is also called the net diversification rate. Here, $\lambda(t)$, $\mu(t)$ and $\delta(t)$ are assumed to be instantaneous rates. Given two dates $t_1$ and $t_2$, we can compute the cumulative rates $\lambda(t_1, t_2) = \int_{t_1}^{t_2} \lambda(t) dt$, $\mu(t_1, t_2) = \int_{t_1}^{t_2} \mu(t) dt$, and $\delta(t_1, t_2) = \int_{t_1}^{t_2} \delta(t) dt$. We derive the average rate by dividing the cumulative rate by the time interval. For example, the average net diversification rate is equal to:

$$\bar{\delta}(t_1, t_2) = \frac{\delta(t_1, t_2)}{t_2 - t_1} = \frac{1}{t_2 - t_1} \int_{t_1}^{t_2} \delta(t) dt$$

In Figures 5 and 6, we report the origination, extinction, and net diversification rates calculated by Rohde and Muller (2005) from the Sepkoski database. For example, the range of the net diversification rate $\delta(t_1, t_2)$ is between -49% and +66%. However, these numbers are difficult to compare because they represent time periods ranging from one million years to seven million years.

The previous remark indicates that we need to normalize the extinction (and other) rates. These rates can be expressed as a percentage per decade, century, or millennium. For long-term trends based on fossil records, we typically express them as a percentage per million years. For example, if the extinction rate $\mu$ is constant and equals 1% per century, this is equivalent to an extinction rate of:

$$\mu = \frac{1\%}{1 \text{ century}} = \frac{1\%}{100 \text{ years}} = 0.01\% \text{ per year}$$

If we assume that the speciation rate is zero, then the number of surviving species follows an exponential survival function:

$$S(t) = \frac{N(t)}{N_0} = e^{-\mu t} \qquad (2)$$

We deduce that the lifespan (or average lifetime) of species is the inverse of the extinction rate:

$$\tau = \frac{1}{\mu}$$
For example, if the extinction rate of a genus is 0.1% per millennium, we obtain:

$$ \tau = \frac{1000 \text{ years}}{0.1\%} = 10^6 \text{ years (or 1 million years)} $$

The lifespan of this genus is then one million years. Pimm et al. (1995) introduced a new metric $\eta$ for assessing extinction rates. They use the number of extinctions (E) per million species per year (MSY) or E/MSY. The relationship between $\eta$, $\mu$ and $\tau$ is then:

$$ \eta = 10^6 \mu = \frac{10^6}{\tau} $$

For example, if $\mu$ is 0.1% per millennium, we get:

$$ \eta = \frac{0.1\%}{10^3 \text{ years}} \times 10^6 = \frac{10^{-3}}{10^3 \text{ years}} \times 10^6 = 1 \text{ E/MSY} $$

If there are 1 million species, the number of extinctions per year would be one. Because scientists use these three metrics $\eta$, $\mu$, and $\tau$ interchangeably to assess extinction rates, it is crucial to understand their definitions and how to convert one metric to another.

**Remark 2** We consider the previous example where the extinction rate of a genus equals 1% per century or 0.01% per year. We get:

$$ \mu = \frac{1\%}{1 \text{ century}} = \frac{1\%}{10^2 \text{ years}} \times \frac{10^6}{10^6} = 10\,000\% \text{ per million years} $$

This example shows that we must be careful with conversion formulas because they ignore the compound effect. Using Equation 2, we deduce that<fnref n="19" />:

$$ \mu^* = -\frac{1}{t} \ln \left( \frac{N(t)}{N_0} \right) = -\frac{1}{t} \ln \left( 1 - \frac{N_0 - N(t)}{N_0} \right) = -\frac{1}{t} \ln \left( 1 - \frac{N^+(t)}{N_0} \right) $$

where $N^+(t)$ is the number of extinctions between 0 and $t$. This formula was proposed by Spalding and Hull (2021) to calculate the extinction rate for long timescales.

**Example 1** We consider three datasets with different species:

<table><thead><tr><th>Species</th><th>N<sub>0</sub></th><th>&Delta;N<sup>+</sup></th><th>&Delta;N<sup>-</sup></th><th>&Delta;t</th></tr></thead><tbody><tr><td>Birds</td><td>5 000</td><td>7</td><td>5</td><td>10 years</td></tr><tr><td>Insects</td><td>75 000</td><td>25</td><td>50</td><td>3 centuries</td></tr><tr><td>Plants</td><td>10<sup>6</sup></td><td>30 &times; 10<sup>3</sup></td><td>15 &times; 10<sup>3</sup></td><td>1 millennium</td></tr></tbody></table>

where $N_0$ is the number of species at the beginning of the period, and $\Delta N^+$ and $\Delta N^-$ are the number of new and dead species during the period $\Delta t$.

The calculated values of $\lambda$, $\mu$, and $\delta$ are shown in the table below. For example, the net diversification rate for the bird species is 0.004% per year, or 4% per millennium. In this example, it is better to use a longer time unit (millennium instead of year) because of the magnitude of the rates.

<table><thead><tr><th>Species</th><th>&lambda;</th><th>&mu;</th><th>&delta;</th><th>&lambda;</th><th>&mu;</th><th>&delta;</th></tr><tr><td></td><td colspan="3" style="text-align: center;">(in % per year)</td><td colspan="3" style="text-align: center;">(in % per millennium)</td></tr></thead><tbody><tr><td>Birds</td><td>0.01400</td><td>0.01000</td><td>0.00400</td><td>14.00</td><td>10.00</td><td>4.00</td></tr><tr><td>Insects</td><td>0.00011</td><td>0.00022</td><td>-0.00011</td><td>0.11</td><td>0.22</td><td>-0.11</td></tr><tr><td>Plants</td><td>0.00300</td><td>0.00150</td><td>0.00150</td><td>3.00</td><td>1.50</td><td>1.50</td></tr></tbody></table>

<footnote n="19">¹⁹To distinguish the logarithmic approach from the arithmetic approach, we use the symbol $\mu^*$ instead of $\mu$. We also define $\tau^* = 1/\mu^*$ and $\eta^* = 10^6\mu^* = 10^6/\tau^*$.</footnote>
We now focus on the extinction rate and calculate this metric with different units. $\mu(0, \Delta t)$ is the cumulative extinction rate. For the bird and plant species, it is equal to:

$$ \mu_{\text{bird}}(0, \Delta t) = \frac{5}{5\,000} = 0.1\% $$

and:

$$ \mu_{\text{plant}}(0, \Delta t) = \frac{15 \times 10^3}{10^6} = 1.5\% $$

These two rates cannot be directly compared because the time periods over which the extinction rate is assessed are very different (10 years versus 1 millennium). Therefore, it is important to normalize. The extinction rate $\mu$ is then expressed in % per year. We can also calculate the extinction rate $\mu^*$ using the previous logarithmic formula. These two extinction rates can then be converted in lifetime (expressed in years) and E/MSY. Numerical results are given below:

<table><thead><tr><th>Species</th><th>μ (0, Δt)<br>(in %)</th><th>μ<br>(in % per year)</th><th>μ<sup>*</sup></th><th>τ<br>(in years)</th><th>τ<sup>*</sup></th><th>η<br>(in E/MSY)</th><th>η<sup>*</sup></th></tr></thead><tbody><tr><td>Birds</td><td>0.10000</td><td>0.01000</td><td>0.01401</td><td>10 000</td><td>7 138</td><td>100.0</td><td>140.1</td></tr><tr><td>Insects</td><td>0.06667</td><td>0.00022</td><td>0.00011</td><td>450 000</td><td>899 850</td><td>2.2</td><td>1.1</td></tr><tr><td>Plants</td><td>1.50000</td><td>0.00150</td><td>0.00305</td><td>66 667</td><td>32 831</td><td>15.0</td><td>30.5</td></tr></tbody></table>

Several observations can be made. First, the figures for $\mu(0, \Delta t)$ cannot be compared directly due to their lack of normalization. We observe extinction rates of 0.1%, 0.07% and 1.5% for birds, insects, and plants, respectively, but these values correspond to different time periods: ten years, three centuries, and one millennium. Second, the results obtained using the arithmetic approach differ from those using the logarithmic approach. Finally, the lifetime and E/MSY figures are probably the easiest to interpret. For example, among one million species, we observe 100, 2.2, and 15 extinctions per year for birds, insects, and plants.

### 1.2.2 Background extension rate

The background extension rate is the normal or typical extension rate that has occurred over the past 500 million years. By normal, we mean the long-term rate at which species would go extinct in the absence of human presence. Thus, most estimates use data up to 1 500 AD. In a brief communication, Simpson (1952) estimated the average duration of a species to be between 0.5 and 5 million years. This was one of the first publications on the subject. For marine invertebrates, Valentine (1970) estimated the average lifetime to be between 5 and 10 million years. The publication of Van Valen (1973) marked a turning point and generated considerable controversy. In this influential paper, the author introduced the concept of Van Valen's Law, which states that extinction rates within a given taxonomic group remain constant over time. To explain this pattern, he proposed the Red Queen hypothesis, which suggests that species must constantly evolve to keep up with competitors and predators. This ongoing evolutionary arms race results in a constant extinction rate. Van Valen (1973, Table 1) calculated the background extinction rate for 20 families, 38 genera, and 3 species. His results satisfy the following coherent inequalities:

$$ \tau_{\text{family}} \ge \tau_{\text{genus}} \ge \tau_{\text{species}} $$

We report some of his estimates<fnref n="20" /> in Table 5. The work of Pimm et al. (1995) was a major milestone in the study of background extinction rates. Based on an analysis of 11 studies, they estimated the

<footnote n="20">²⁰Van Valen (1973) used the macarthur (ma) measure to define the lifespan of species. One macarthur is the rate of extinction given a half-life of 500 years. Since the figures reported by Van Valen are expressed in micromacarthurs ($\mu$ma), we estimate the lifespan in million years using the following formula: $\tau = 500/(\mu \ln 2)$ where $\mu$ is the extinction rate in $\mu$ma.</footnote>
<table><caption>Table 5: Estimates of the background extension rate $\bar{\eta}$</caption><thead><tr><th>Taxonomy</th><th>τ (in myr)</th><th>η (in E/MSY)</th><th>Source</th></tr></thead><tbody><tr><td>All species</td><td>1 – 10</td><td>0.10 – 1.00</td><td>Pimm et al. (1995)</td></tr><tr><td>All species</td><td>1.0</td><td>0.10</td><td>De Vos et al. (2015)</td></tr><tr><td>All fossil groups</td><td>0.5 – 5</td><td>0.20 – 2.00</td><td>Simpson (1952)</td></tr><tr><td>Marine fossil groups</td><td>7.4 – 20</td><td>0.05 – 0.13</td><td>Raup and Sepkoski (1982)</td></tr><tr><td>Marine invertebrates</td><td>5 – 10</td><td>0.10 – 0.20</td><td>Valentine (1970)</td></tr><tr><td>Cetacea (genus)</td><td>3.61</td><td>0.277</td><td>Van Valen (1973)</td></tr><tr><td>Devonian & Cenozoic bivalves</td><td>6.5 – 9.7</td><td>0.10 – 0.15</td><td>Valentine (1970)</td></tr><tr><td>Silurian graptolites</td><td>2.0 – 3.0</td><td>0.33 – 0.50</td><td>Rickards (1977)</td></tr><tr><td>Diatoms</td><td>8.02</td><td>0.125</td><td>Van Valen (1973)</td></tr><tr><td>Dinoflagellata</td><td>13.12</td><td>0.076</td><td>Van Valen (1973)</td></tr><tr><td>Foraminifera (planktonic)</td><td>7.21</td><td>0.139</td><td>Van Valen (1973)</td></tr><tr><td>Foraminifera (genus)</td><td>24.04</td><td>0.042</td><td>Van Valen (1973)</td></tr><tr><td>Foraminifera (family)</td><td>72.13</td><td>0.014</td><td>Van Valen (1973)</td></tr><tr><td>Arthropods</td><td>1.07 – 11.11</td><td>0.090 – 0.934</td><td>De Vos et al. (2015)</td></tr><tr><td>Chordates</td><td>1.71 – 15.63</td><td>0.064 – 0.586</td><td>De Vos et al. (2015)</td></tr><tr><td>Mammals</td><td>0.56</td><td>1.800</td><td>Barnosky et al. (2011)</td></tr><tr><td>Mammals & birds</td><td>0.55 – 4.80</td><td>0.208 – 1.818</td><td>Loehle and Eschenbach (2012)</td></tr><tr><td>Mammals</td><td>9.80 – 43.48</td><td>0.023 – 0.102</td><td>De Vos et al. (2015)</td></tr><tr><td>Mammals</td><td>0.50</td><td>2.000</td><td>Ceballos et al. (2015)</td></tr><tr><td>Mollusca</td><td>0.60 – 7.41</td><td>0.135 – 1.672</td><td>De Vos et al. (2015)</td></tr><tr><td>Primates (genus)</td><td>3.28</td><td>0.305</td><td>Van Valen (1973)</td></tr><tr><td>Reptilia (family)</td><td>24.05</td><td>0.042</td><td>Van Valen (1973)</td></tr><tr><td>Plants</td><td>2.84 – 18.87</td><td>0.053 – 0.352</td><td>De Vos et al. (2015)</td></tr><tr><td>Plants</td><td>7.69 – 20.00</td><td>0.050 – 0.130</td><td>Gray (2019)</td></tr></tbody></table>

background rate $\bar{\eta}$ to be between 0.1 and 1 E/MSY. Since then, the 1 E/MSY benchmark has been widely adopted in many mass extinction studies. However, it's important to note that this benchmark can vary depending on the specific species or taxonomic group being considered. For example, Barnosky et al. (2011) proposed a benchmark of 1.8 E/MSY for mammals. De Vos et al. (2015) conducted a comprehensive study across different taxa (arthropods, chordates, mammals, mollusca, and plants) and suggested that the lower bound of the Pimm et al. (1995) estimate is a more appropriate benchmark, namely $\bar{\eta} = 0.1$ E/MSY.

### 1.2.3 Mass extinction

A mass extinction is a widespread and rapid decline in Earth's biodiversity (genetic or species diversity), during which a substantial proportion of the planet's species disappear over a relatively short period of time — typically thousands to millions of years, which is short on the geologic time scale. The characterization of an extinction event is then determined using calculated extinction rates. Mathematically, we have:

$$[t_1, t_2] \text{ is an extinction event period} \Leftrightarrow \mu(t_1, t_2) \ge \mu^* \text{ and } \bar{\eta}(t_1, t_2) \gg \bar{\eta} \quad (3)$$

where $\mu(t_1, t_2)$ is the (total) extinction rate expressed in % during the period $[t_1, t_2]$, $\bar{\eta}(t_1, t_2)$ is the mean extinction rate expressed in E/MSY, $\mu^*$ is a threshold value and $\bar{\eta}$ is the background rate. For
example, $\mu^* = 30\%$ means that 30% of species must disappear between times $t_1$ and $t_2$ for the period $[t_1, t_2]$ to be characterized as an extension event. Although there is no consensus on the threshold, scientists generally use a minimum of 30% for species and 15% for families to characterize a mass extinction.

Using fossil data records, Raup and Sepkoski (1982) demonstrated that four mass extinctions in the marine realm — occurring in the late Ordovician, Permian, Triassic, and Cretaceous periods — had extinction rates that were statistically significantly higher than background rate levels. However, this was not the case for a fifth extinction event in the Devonian. Benton (1995) used a new database that included both marine and continental fossil records and examined 22 extinction events. His results showed that extinction rates can be very different for marine and continental organisms. The study of Bambach (2006) identifies eighteen extinctions and comes to the same conclusion:

> "A review of different methods of tabulating data from the Sepkoski database reveals 18 intervals during the Phanerozoic have peaks of both magnitude and rate of extinction that appear in each tabulating scheme. These intervals all fit Sepkoski's definition of mass extinction. However, they vary widely in timing and effect of extinction, demonstrating that mass extinctions are not a homogeneous group of events." (Bambach, 2006, page 127).

For this reason, paleontologists often use a scale to categorize mass extinction events, distinguishing between<fnref n="21" />:

* Small extinction events: Relatively minor events that do not drastically alter biodiversity;

* Pulse events: More pronounced extinctions that can significantly impact certain taxonomic groups;

* The 'Big Five' extinctions: The five major mass extinctions in Earth's history that resulted in a significant loss of biodiversity.

The Big Five extinctions are those identified by Raup and Sepkoski (1982). For each event, we report below some figures<fnref n="22" /> on the total extinction rate<fnref n="23" /> and the possible causes:

1. Ordovician-Silurian mass extinction — LOME (445–443 Myr BP)
About 27% of all families, 57% of all genera and 85% of all species became extinct. It is generally assumed that the cause is climate change (global cooling) and volcanic activity, which affect the chemistry of the atmosphere and oceans and CO₂ sequestration.

<footnote n="21">²¹For more informations and illustrations, the reader can consult Chapter 7 of Primack (2014) for detailed information on extinction with a lot of numbers and examples.</footnote>

<footnote n="22">²²Following the terminology of Algeo and Shen (2024), we use the following abbreviations for the five major mass extinctions: LOME for Late Ordovician, LDME for Late Devonian, EPME for end-Permian, ETME for end-Triassic and ECME for end-Cretaceous mass extinctions. Other commonly used abbreviations include: O-S for Ordovician-Silurian, L-D for Late Devonian, P-T for Permian-Triassic, T-J for Triassic-Jurassic, K-Pg for Cretaceous-Paleogene (previously called K-T for Cretaceous-Tertiary) extinctions. It's important to note that a mass extinction period can be characterized by multiple extinction events. According to Benton (1995), the Big Five extinctions can be further broken down as follows: 1 event for LOME (Ashgillian), 2 events for LDME (Givetian-Frasnian & Famennian), 3 events for EMPE (Ufimian, Kazanian-Tatarian & Tatarian), 3 events for ETME (Carnian, Norian-Rhaetian & Rhaetian) and 2 events for ECME (Cenomanian & Maastrichtian).</footnote>

<footnote n="23">²³These figures come from the Wikipedia page (https://en.wikipedia.org/wiki/Extinction_event) and are based on the book of Benton (2015). These estimates should be treated with caution, as they may vary from study to study. For example, Barnosky et al. (2011) estimated extinction rates for genera and species to be 57% and 86% for LOME, 35% and 75% for LDME, 56% and 96% for EPME, 47% and 80% for ETME, and 40% and 76% for ECME, respectively. However, we observe that the order of magnitude is the same in most studies.</footnote>
2. Late Devonian mass extinction — LDME (372–359 Myr BP)
About 19% of all families, 35-50% of all genera and 75% of all species became extinct. The cause is generally thought to be climate change (global cooling followed by global warming) and the removal of global CO2.

3. Permian-Triassic extinction or ‘*The Great Dying*’ — EPME (252–251 Myr BP)
About 57% of marine families, 84% of marine genera, 81% of all marine species and 90% of terrestrial vertebrate species became extinct. The cause is generally thought to be climate change (global warming) and volcanic activity (massive volcanic eruptions in Siberia).

4. Triassic-Jurassic extinction — ETME (200–201 Myr BP)
About 23% of all families, 48% of all genera (20% of marine families and 55% of marine genera) and 70-75% of all species became extinct. It is generally thought to be caused by volcanic activity (massive volcanic eruptions in the Central Atlantic Magmatic Province) and sea level changes.

5. Cretaceous-Paleogene extinction — ECME (66 Myr BP)
About 17% of all families, 47% of all genera and 75% of all species became extinct. The Cretaceous extinction is marked by the disappearance of the Dinausores. It is generally assumed that the cause is an asteroid impact followed by widespread environmental disruption, including tsunamis, forest fires, and climate change.

We find that the causes, while diverse, are related to a small number of natural phenomena:

> "Every mass extinction has both an ultimate cause, i.e., the trigger that leads to various climato-environmental changes, and one or more proximate cause(s), i.e., the specific climato-environmental changes that result in elevated biotic mortality. With regard to ultimate causes, strong cases can be made that bolide (i.e., meteor) impacts, large igneous province eruptions and bioevolutionary events have each triggered one or more of the Phanerozoic Big Five mass extinctions, and that tectono-oceanic changes have triggered some second-order extinction events. [...] With regard to proximate mechanisms, most extinctions are related to either carbon-release or carbon-burial processes, the former being associated with climatic warming, ocean acidification, reduced marine productivity and lower carbonate δ¹³C values, and the latter with climatic cooling, increased marine productivity and higher carbonate δ¹³C values." (Algeo and Shen, 2024, page 1).

The leading hypothesis for the fifth mass extinction is the impact of a large asteroid that struck the Earth near the Yucatán Peninsula in Mexico, forming the Chicxulub crater (Schulte et al., 2010). The asteroid, estimated to be 10 to 15 kilometers in diameter, released an immense amount of energy, equivalent to billions of nuclear bombs. This catastrophic impact caused massive earthquakes, tsunamis, and forest fires. In addition, the impact likely caused a ‘nuclear winter’ as a massive plume of debris and vaporized rock was ejected into the atmosphere and spread globally. This debris blocked sunlight, leading to a drastic cooling of the planet, reduced photosynthesis, and a collapse of food chains. While the asteroid impact hypothesis is widely accepted, other factors such as climate change and volcanic activity may also have contributed to the Cretaceous-Paleogene mass extinction. Interestingly, this extinction paved the way for the rise of mammals, including humans, as it wiped out the dinosaurs that had previously dominated the planet. As shown in Figure 5 on page 19, biodiversity tends to rebound significantly after each mass extinction. Although biodiversity loss is generally followed by strong gains, this recovery occurs on the paleontological timescale of millions of years.
Box 3: IUCN Red List of Threatened Species

Founded in 1964, the International Union for Conservation of Nature (IUCN) is responsible for maintaining and updating the IUCN Red List of Threatened Species. It is now considered the world's most comprehensive source of information on the global extinction status of animals, fungi and plants. They correspond to three kingdoms in organismal diversity or modern biological taxonomy, the other two being protista (single-celled eukaryota) and monera (single-celled prokaryota). IUCN (2012) assesses the risk status of a species according to the following A-E criteria: (A) population size reduction (population decline measured over the longer of 10 years or 3 generations, trend), (B) geographic range (extent of occurrence, area of occupancy), (C) small population size and decline (number of mature individuals, trend), (D) very small or restricted population (number of mature individuals, number of locations), and (E) quantitative analysis (probability of extinction). The Red List divides then species into nine categories:

* **Not Evaluated (NE) & Data Deficient (DD)**

A taxon is NE if it has not yet been evaluated against the criteria. NE species are not published in the IUCN Red List. A taxon is DD if there is insufficient information to make a direct or indirect assessment of its risk of extinction based on its distribution and/or population status. A taxon in this category may be well studied and its biology well understood, but adequate data on abundance and/or distribution are lacking.

* **Least Concern (LC) & Near Threatened (NT)**

A taxon is LC if it has been assessed against the Red List criteria and is not considered CR, EN, VU or NT. A taxon is NT if it has been evaluated against the criteria, but does not currently qualify as CR, EN, or VU, but is close to or is likely to qualify for a threatened category in the near future.

* **Vulnerable (VU), Endangered (EN) & Critically Endangered (CR)**

A taxon is VU (EN or CR, respectively) if the best available evidence indicates that it meets any of the criteria A to E for VU and is therefore considered to be at high (very high or extremely high, respectively) risk of extinction in the wild.

* **Extinct in the Wild (EW)**

A taxon is EW if it is known to survive only in cultivation, captivity, or as a naturalized population (or populations) far outside its historical range. A taxon is presumed to be EW if exhaustive surveys in known and/or expected habitats at appropriate times (diurnal, seasonal, annual) throughout its historical range have failed to record an individual. Surveys should be conducted over a period of time appropriate to the life cycle and life form of the taxon.

* **Extinct (EX)**

A taxon is EX when there is no reasonable doubt that the last individual has died. A taxon is presumed EX when exhaustive surveys in known and/or expected habitat at appropriate times (diurnal, seasonal, annual) throughout its historical range have failed to record an individual. Surveys should be conducted over a period of time appropriate to the life cycle and life form of the taxon.
1.2.4 The Holocene extinction, the Anthropocene extinction or the sixth mass extinc-
tion?

At the October 1991 symposium *The Visions of a Sustainable World* at Caltech, Edward O. Wilson warned that “we are now in the midst of a sixth extinction spasm, the greatest since the one that closed the age of the dinosaurs 66 million years ago.” In 1995, Richard Leakey published the book *The Sixth Extinction*, which popularized the term in the scientific community (Leakey and Lewin, 1995). Since then, numerous research papers have been published (Pimm and Brooks, 2000; Wake and Vredenburg, 2008; Barnosky et al., 2011; Dirzo et al., 2014; Ceballos et al., 2015; Cowie et al., 2022). However, it was Elizabeth Kolbert’s book *The Sixth Extinction: An Unnatural History*, which won the Pulitzer Prize in 2015, that introduced the term to the general public (Kolbert, 2014).

There is no doubt that the extinction rate observed since 1500 AD is largely higher than the background rate, as demonstrated by Pimm et al. (1995, page 347) (“recent extinction rates are 100 to 1000 times their pre-human levels in well-known, but taxonomically diverse groups from widely different environments”), and De Vos et al. (2015, page 452) (“current extinction rates are 1000 times higher than natural background rates of extinction and future rates are likely to be 10 000 times higher”). This is true for both terrestrial and marine extinctions (Ceballos et al., 2017; Del Monte-Luna et al., 2023). This is why we can speak of a Holocene extinction. There is also no doubt that this extinction event is due to humans, leading to the concept of Anthropocene extinction or defaunation (Dirzo et al., 2014). However, it is still difficult to definitively classify our current epoch as the sixth mass extinction. While we meet the criterion for the elevated background extinction rate based on relation (3), we have yet to confirm the condition $\mu (t_1, t_2) \ge \mu^*$. Therefore, there is no scientific research that claims that more than 75% of all marine and terrestrial vertebrate species have become extinct in the last five centuries or in the last 10 000 years. We do not really know. Moreover, a mass extinction is usually followed by a period of intense species origination. Therefore, it is difficult to say that the sixth mass extinction has already occurred (Barnosky et al., 2011). The majority of scientists prefer to argue that “we are either entering or in the midst of the sixth great mass extinction” (Wake and Vredenburg, 2008).

Why are we talking about the sixth mass extinction? Because the number of species that have become extinct in the last few centuries is so large, these extinctions are due to human activities, and we do not expect these extinctions to stop in the next few years with population growth and deforestation. The trends are dramatic and we are clearly facing a biodiversity crisis. These facts are extensively documented in the research cited above, as well as in the monumental 1148-page report by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, 2019).

The stylized facts about current extinction rates are based on the IUCN Red List of Threatened Species (Box 3). As of September 2024, the current Red List database contains 163 040 species whose extinction risk has been assessed. For each species, we can obtain the assessment report by using the search query https://www.iucnredlist.org/search. For example, the figures for the snow leopard are available at www.iucnredlist.org/species/22732/50664030. We learned that the snow leopard species (*Panthera uncia*) was assessed in November 2016. Panthera uncia is currently listed as VU (Vulnerable), whereas in 2008 it was listed as EN (Endangered). Much more information can be found in its assessment card<fnref n="24" />.

<footnote n="24">²⁴The snow leopard belongs to the following taxonomic classification tree: Animalia (kingdom), Chordata (phylum), Mammalia (class), Carnivora (order), Felidae (family), Panthera (genus), and Panthera uncia (species). The number of mature individuals is estimated to be between 2 710 and 3 386, with a decreasing population trend. It is found in Asia, including Afghanistan, Bhutan, China, India, Kazakhstan, Kyrgyzstan, Mongolia, Nepal, Pakistan, the Russian Federation, Tajikistan, and Uzbekistan. The Panthera uncia inhabits altitudes between 500 and 5 800 meters. Its home</footnote>
<figure><img src="image_10.png" /><figcaption>Figure 7: Number of extinct species since 1500 AD</figcaption></figure>

Source: IUCN (2024a), www.iucnredlist.org & Author's calculations.

Among the 163 040 species evaluated, 908 are extinct, with the following distribution: 85.6% from Animalia and 14.4% from Plantae (Table 6). This corresponds to an extinction rate of 0.56%. Most of these extinct species belong to four phyla: Chordata, Mollusca, Arthropoda, and Tracheophyta (Figure 7). Within the Chordata phylum, the class Aves (birds) is the most represented, followed by Mammalia, Actinopterygii (ray-finned fishes), Amphibia, and Reptilia. In the Mollusca phylum, most extinct species are in the class Gastropoda, with the remainder in Bivalvia. In the Tracheophyta phylum, the class Magnoliopsida is the most dominant. Some examples of extinct species are the Dodo, the Splendid Poisson Frog, the Floreana Giant Tortoise, the St Helena Olive, the Stringwood and the Galapagos Amaranth.

Table 6 shows the breakdown of the 163 040 evaluated species according to the IUCN Red List categories. There are 81 species classified as Extinct in the Wild (EW), with a balanced distribution between Animalia and Plantae. Examples of EW species include the Spix's Macaw, the Polynesian Tree Snail, the Golden Skiffia, the Yellow Fatu, the Superb Cyanea, and Wood's Cycad. A similar distribution between Animalia and Plantae is observed for Critically Endangered (CE) species, but their number is much larger, totaling 10 031 species. Examples include the Hainan Gibbon, the Golden Line Fish, the Gomera Stick Grasshopper, the Didymous Chamomile, the French Grass, and the Hawaiian Gardenia.

According to IUCN (2024b), the number of threatened species (TH) is defined as follows:

$$TH = EW + CR + EN + VU$$

<footnote>range is estimated to be about 2.8 million km² and its generation length is approximately 7.54 years. Additionally, a list of threats and conservation actions has been documented.</footnote>
<table><caption>Table 6: Statistics of the IUCN Red List database</caption><thead><tr><th>Kingdom</th><th>Animalia</th><th>Chromistra</th><th>Fungi</th><th>Plantae</th><th>Total</th></tr></thead><tbody><tr><td>Extinct</td><td>777</td><td></td><td></td><td>131</td><td>908</td></tr><tr><td>Extinct in the Wild</td><td>36</td><td></td><td></td><td>45</td><td>81</td></tr><tr><td>Critically Endangered</td><td>4 067</td><td>4</td><td>45</td><td>5 915</td><td>10 031</td></tr><tr><td>Endangered</td><td>6 426</td><td>1</td><td>105</td><td>11 477</td><td>18 009</td></tr><tr><td>Vulnerable</td><td>7 165</td><td>1</td><td>178</td><td>9 937</td><td>17 281</td></tr><tr><td>Conservation Dependent</td><td>18</td><td></td><td></td><td>114</td><td>132</td></tr><tr><td>Near Threatened</td><td>5 149</td><td></td><td>66</td><td>4 203</td><td>9 418</td></tr><tr><td>Least Concern</td><td>51 689</td><td></td><td>240</td><td>33 373</td><td>85 302</td></tr><tr><td>Data Deficient</td><td>15 895</td><td>12</td><td>160</td><td>5 811</td><td>21 878</td></tr><tr><td>Total</td><td>91 222</td><td>18</td><td>794</td><td>71 006</td><td>163 040</td></tr></tbody></table>

Source: IUCN (2024a), www.iucnredlist.org & Author's calculations.

<table><caption>Table 7: Number of species assessed and number of threatened species by major group of organisms</caption><thead><tr><th>Taxon</th><th>Clade</th><th>Number of species</th><th colspan="2">Evaluated species</th><th colspan="2">Threatened species</th></tr><tr><th></th><th></th><th></th><th>#</th><th>%</th><th>#</th><th>%</th></tr></thead><tbody><tr><td rowspan="6">Vertebrates</td><td>Mammals</td><td>6 701</td><td>5 983</td><td>89.3%</td><td>1 338</td><td>22.4%</td></tr><tr><td>Birds</td><td>11 195</td><td>11 195</td><td>100.0%</td><td>1 354</td><td>12.1%</td></tr><tr><td>Reptiles</td><td>12 162</td><td>10 309</td><td>84.8%</td><td>1 844</td><td>17.9%</td></tr><tr><td>Amphibians</td><td>8 744</td><td>8 011</td><td>91.6%</td><td>2 873</td><td>35.9%</td></tr><tr><td>Fishes</td><td>36 863</td><td>27 972</td><td>75.9%</td><td>3 927</td><td>14.0%</td></tr><tr><td>Subtotal</td><td>75 665</td><td>63 470</td><td>83.9%</td><td>11 336</td><td>17.9%</td></tr><tr><td rowspan="10">Invertebrates</td><td>Insects</td><td>1 053 578</td><td>12 718</td><td>1.2%</td><td>2 415</td><td>19.0%</td></tr><tr><td>Molluscs</td><td>86 859</td><td>9 111</td><td>10.5%</td><td>2 451</td><td>26.9%</td></tr><tr><td>Crustaceans</td><td>90 531</td><td>3 213</td><td>3.5%</td><td>747</td><td>23.2%</td></tr><tr><td>Corals</td><td>5 623</td><td>831</td><td>14.8%</td><td>252</td><td>30.3%</td></tr><tr><td>Arachnids</td><td>95 894</td><td>774</td><td>0.8%</td><td>272</td><td>35.1%</td></tr><tr><td>Velvet Worms</td><td>222</td><td>11</td><td>5.0%</td><td>9</td><td>81.8%</td></tr><tr><td>Horseshoe Crabs</td><td>4</td><td>4</td><td>100.0%</td><td>2</td><td>50.0%</td></tr><tr><td>Others</td><td>157 543</td><td>1 090</td><td>0.7%</td><td>174</td><td>16.0%</td></tr><tr><td>Subtotal</td><td>1 490 254</td><td>27 752</td><td>1.9%</td><td>6 322</td><td>22.8%</td></tr><tr><td rowspan="7">Plants</td><td>Mosses</td><td>21 925</td><td>327</td><td>1.5%</td><td>181</td><td>55.4%</td></tr><tr><td>Ferns and Allies</td><td>11 800</td><td>821</td><td>7.0%</td><td>321</td><td>39.1%</td></tr><tr><td>Gymnosperms</td><td>1 113</td><td>1 059</td><td>95.1%</td><td>451</td><td>42.6%</td></tr><tr><td>Flowering Plants</td><td>369 000</td><td>68 704</td><td>18.6%</td><td>26 367</td><td>38.4%</td></tr><tr><td>Green Algae</td><td>13 960</td><td>17</td><td>0.1%</td><td>0</td><td>0.0%</td></tr><tr><td>Red Algae</td><td>7 523</td><td>78</td><td>1.0%</td><td>9</td><td>11.5%</td></tr><tr><td>Subtotal</td><td>425 321</td><td>71 006</td><td>16.7%</td><td>27 329</td><td>38.5%</td></tr><tr><td rowspan="3">Fungi</td><td>Mushrooms, etc.</td><td>156 313</td><td>794</td><td>0.5%</td><td>328</td><td>41.3%</td></tr><tr><td>Brown Algae</td><td>4 683</td><td>18</td><td>0.4%</td><td>6</td><td>33.3%</td></tr><tr><td>Subtotal</td><td>160 996</td><td>812</td><td>0.5%</td><td>334</td><td>41.1%</td></tr><tr><td colspan="2">Total</td><td>2 152 236</td><td>163 040</td><td>7.6%</td><td>45 321</td><td>27.8%</td></tr></tbody></table>

Source: IUCN (2024b, Table 1a), www.iucnredlist.org & Author's calculations.
It is usually expressed in %:

$$TH(\%) = \frac{TH}{TOT - EX - DD} = \frac{EW + CR + EN + VU}{TOT - EX - DD}$$

where TOT is the total number of species assessed<fnref n="25" />. We deduce that:

$$TH = 81 + 10031 + 18009 + 17281 = 45402$$

In Table 7 we reproduce the calculations that can be found in IUCN (2024b, Table 1a). In this case, the number of threatened species does not include the EW category, which means that:

$$TH^* = 10031 + 18009 + 17281 = 45321$$

The percentage of threatened species is 27.8%. Excluding the clades with low population numbers, we conclude that two categories are particularly threatened: Amphibians and flowering plants with a threat rate of 35.9% and 38.4% respectively. Figure 8 shows the evolution of the number of threatened species over time. Over the past 24 years, the number of threatened species has increased by 310%, which corresponds to an annual growth rate of 6.1%. This graph is widely cited and can be found in numerous publications on the current biodiversity crisis. However, caution is needed. A significant part of this trend is due to the fact that the database has become more comprehensive over time. For instance, the IUCN Red List aims to assess 260 000 species and reassess 142 000 of those already assessed by 2030. Naturally, the number of threatened species will rise as the database's coverage increases. For this reason, we have included the proportion of threatened species in Figure 9. Since 2010, this proportion has remained stable at around 30%.

However, the previous observation could not hide the fact that the current biodiversity crisis is real and serious, and that we may be in a sixth mass extinction period. There are so many facts that demonstrate this critical situation (Barnosky et al., 2011; Ceballos et al., 2015; Cowie et al., 2022). A major challenge in addressing the current biodiversity crisis is the concept of 'extinction debt' (Kuussaari et al., 2009; Figueiredo et al., 2019). This refers to the delayed extinction of species following environmental changes such as habitat loss, fragmentation or degradation. Despite these threats, species may persist for years, decades, or even centuries before succumbing to extinction. This lag creates a debt, where species are essentially doomed, but survive temporarily in their environment. Therefore, extension debt is related to habitat loss and relaxation time:

> "The idea that species can initially survive habitat change but later become extinct without any further habitat modification has a long history. It was first conceptualized in island biogeography (MacArthur and Wilson, 1967) and further elaborated by Jared Diamond, who introduced the term relaxation time as the delay of expected extinctions after habitat loss. According to theoretical predictions and supporting empirical data, the relaxation time increases with increasing patch area and with decreasing isolation. A second root stems from metapopulation modeling. Tilman et al. (1994) introduced the term extinction debt and considered the order of extinctions in relation to competitive dominance [...] The concept of extinction debt is related to relaxation time but specifies the number or proportion of extant species predicted to become extinct as the species community reaches a new equilibrium after an environmental perturbation." (Kuussaari et al., 2009, page 565).

<footnote n="25">²⁵Sometimes the IUCN gives a lower and an upper bound for the estimated percentage of threatened species: LB(%) ≤ TH(%) ≤ UB(%) where LB(%) = $\frac{TH}{TOT-EX}$ = $\frac{EW+CR+EN+VU}{TOT-EX}$ and UB(%) = $\frac{TH}{TOT-EX}$ = $\frac{EW+CR+EN+VU+DD}{TOT-EX}$.</footnote>
<figure><img src="image_11.png" /><figcaption>Figure 8: Number of species in the threatened categories (CR, EN, and VU)</figcaption></figure>

Source: IUCN (2024b, Tables 1.b & 2), www.iucnredlist.org & Author's calculations.

<figure><img src="image_12.png" /><figcaption>Figure 9: Percentage of species in the threatened categories (CR, EN, and VU)</figcaption></figure>

Source: IUCN (2024b, Tables 1.b & 2), www.iucnredlist.org & Author's calculations.
The issue of habitat loss is explored on page 75, while the issue of relaxation time<fnref n="26" /> can be described as follows. Kuussaari et al. (2009, Glossary, page 564) defined the equilibrium (or stable) state in an ecological community when the number of species does not change because the local extinction rate is equal to the local origination rate. The relaxation time scale is then the time to reach a new equilibrium. Assessing the extinction debt for a given species involves estimating whether the species will eventually go extinct and, if so, determining the likely time of extinction. Kuussaari et al. (2009, Box 1, page 567) outline five main approaches for evaluating extinction debt:

* Detection of extinction debt using past and present habitat characteristics;

* Estimating extinction debt by comparing present-day stable and unstable landscapes;

* Estimating extinction debt based on past and present species richness and habitat characteristics;

* Tracking extinction debt based on time series data;

* Evaluating extinction debt for single species using empirical population data and spatially explicit modeling.

The survey of empirical studies on extinction debt by Kuussaari et al. (2009, Table 1, page 568) found inconsistencies across these approaches. For instance, studies using the first approach typically conclude that amphibians are subject to extinction debts, while studies using the second approach often suggest that amphibians are not subject to extinction debts. However, empirical evidence consistently suggests that forest birds, primates, wood-living fungi, and forest beetles are likely to have extinction debts.

In Halley et al. (2016b), it is assumed that the remaining habitat area is reduced from $A_0$ to A, leading to a corresponding decline in species richness to a new value $S(t)$ at time $t$. The equation governing species loss is given by:

$$ \frac{dS(t)}{dt} = \lambda(t) - \mu(t) S(t) \qquad (4) $$

where $\lambda(t)$ is the origination rate and $\mu(t)$ is the extinction date. The remaining habitat contains a (constant) number $N(t)$ of individuals, which is proportional to the area A and the density $\rho$ of individuals per unit area: $N(t) = \rho A$. Let $n(t) = N(t)/S(t)$ be the average population size per species. At time $t=0$, we have $n = N_0/S_0 = \rho A/S_0$ where $S(0) = S_0$ is the initial species richness. The authors further assumed that the extinction rate is described by:

$$ \mu(t) = kn(t)^{-\alpha} = k \left( \frac{S(t)}{N(t)} \right)^{\alpha} $$

Therefore, Equation (4) becomes:

$$ \frac{dS(t)}{dt} = \lambda(t) - k \left( \frac{S(t)}{\rho A} \right)^{\alpha} S(t) = \lambda(t) - \frac{k}{n^{\alpha} S_{0}^{\alpha}} S(t)^{\alpha+1} \qquad (5) $$

The numerical solution can be easily found when the origination rate $\lambda(t)$ is specified. In the case of extinction debt, we can assume that $\lambda(t) = 0$ and the solution is<fnref n="27" />:

$$ S(t) = S_0 \left( 1 + \frac{k\alpha}{n^{\alpha}} t \right)^{-1/\alpha} \qquad (6) $$

<footnote n="26">²⁶The concept of relaxation time is used extensively in equilibrium temperature modeling (see Roncalli (2025, pages 671 and 683)) and bifurcation theory (see Roncalli (2025, page 692).</footnote>

<footnote n="27">²⁷This is derived from the known solution of the differential equation $x'(t) = -bx(t)^{\alpha+1}$ with initial condition $x(0) = x_0$, which is $x(t) = (\alpha bt + x_0^{-\alpha})^{-1/\alpha}$.</footnote>
Figure 10 shows the evolution of the relative species richness for various values of $\alpha$ with fixed parameters $A = 500$, $k = 0.20$, $\rho = 0.90$ and $S_0 = 100$. As the value of $\alpha$ approaches 0, the solution converges to the exponential model, which assumes species richness is independent of population size. In this case we have $S(t) = S_0 e^{-kt}$. When $\alpha$ approaches 1, we obtain the neutral model, where species richness remains constant over time: $S(t) = S_0$. In the other cases $\alpha \in (0, 1)$, the extinction curve follows a hyperbolic trajectory. To understand the effect of time, Halley et al. (2016b) examine the case $\alpha = 0.5$ and show that the extinction debt is inversely proportional to the square of time:

$$S(t) = \frac{S_0}{\left(1 + \frac{k}{2\sqrt{n}}t\right)^2} \sim \frac{2S_0}{k^2}t^{-2}$$

Extinction debt is typically quantified by the relaxation time $\tau$, which represents the time required for species richness to decrease by half. Solving the equation $S(t) = S_0/2$ gives the following solution:

$$S_0 \left(1 + \frac{k\alpha}{n^\alpha}\tau\right)^{-1/\alpha} = \frac{S_0}{2} \Leftrightarrow \tau = (2^\alpha - 1) \frac{n^\alpha}{k\alpha} \propto n^\alpha$$

In the previous example, $\tau$ is equal to 4.2, 8.8 and 18.6, respectively.

<figure><img src="image_13.png" /><figcaption>Figure 10: Relative species richness and relaxation time</figcaption></figure>

The previous analysis assumes no speciation, which means that the equilibrium species richness $\bar{S} = \lim_{t \to \infty} S(t)$ ultimately approaches zero. To get a more realistic model, we now introduce a constant origination rate: $\lambda(t) = \lambda$. The equilibrium state $\bar{S}$ is reached when the rate of change in species richness becomes zero:

$$\frac{dS(t)}{dt} = 0 \Leftrightarrow \lambda - \frac{k}{n^\alpha S_0^\alpha} \bar{S}^{\alpha+1} = 0 \Leftrightarrow \bar{S} = \left(\frac{\lambda n^\alpha S_0^\alpha}{k}\right)^{1/(\alpha+1)}$$
This is the value of the steady state after the reduction of the area to A. Before reducing the area, the steady state $\bar{S}_0$ satisfies the following equation:

$$ \lambda - \frac{k}{n_0^\alpha \bar{S}_0^\alpha} \bar{S}_0^{\alpha+1} = 0 \Leftrightarrow \bar{S}_0 = \left( \frac{\lambda (\rho A_0)^\alpha}{k} \right)^{1/(\alpha+1)} $$

because the original habitat area was $A_0$ and $n_0 = \rho A_0 / \bar{S}_0$. In Figure 11 we illustrate the transition from one steady state to another. We use the following parameters: $A_0 = 1000$, $A = 500$, $k = 0.10$, $\alpha = 0.5$, $\rho = 10$ and $\lambda = 5\%$. Initially, at time $t = -1000$ years, we consider two starting values for species richness: $S(-1000) = 15$ and $S(-1000) = 12$. Both trajectories converge to the steady state value $\bar{S}_0 = 13.572$. At time $t = 0$, we reduce the available habitat by 50%, causing the species richness to shift to a new steady state $\bar{S}_0 = 10.772$. However, it takes time, and the transition between the two equilibria is not instantaneous. It is gradual, resulting in what is known as an extinction debt. The key challenge is to determine whether we are in the early or late stages of this extinction debt process.

<figure><img src="image_14.png" /><figcaption>Figure 11: Extinction debt and steady state</figcaption></figure>

**Remark 3** The modeling of extinction debt, particularly in relation to the current biodiversity crisis, has generated extensive research. Notable contributions include the work of Tilman et al. (1994), Hanski and Ovaskainen (2002, 2003), and more recently, Spalding and Hull (2021) with the pulse event model (Box 4).
Box 4: The Spalding-Hull pulse model

Spalding and Hull (2021) extended the constant birth-death model by introducing extinction pulses:

$$ \mu^{(\text{pulse})}(t) = \mu_0 - \sum_{k=1}^{n^{(\text{pulse})}} \omega_k^{(\text{pulse})} \ln(1 - A_k^{(\text{pulse})}) f_k(t - t_k^{(\text{pulse})}) $$

where $\mu_0$ is the background rate, $n^{(\text{pulse})}$ is the number of pulses, $\omega_k^{(\text{pulse})}$, $A_k^{(\text{pulse})}$ and $t_k^{(\text{pulse})}$ are the scaling factor, the fraction of species removed and the date of the kth extinction pulse event, and $f_k(x)$ is the probability density function. For example, Spalding and Hull (2021) used the Gaussian single pulse model:

$$ \mu^{(\text{pulse})}(t) = \mu_0 - \omega^{(\text{pulse})} \frac{\ln(1 - A^{(\text{pulse})})}{\sigma\sqrt{2\pi}} \exp\left(-\frac{1}{2}\left(\frac{t - t^{(\text{pulse})}}{\sigma}\right)^2\right) $$

where $\sigma$ is the standard deviation controlling the pulse duration. We deduce that:

$$ \begin{aligned} \mathcal{E}(t) &= \frac{1}{\Delta t} \int_{t}^{t+\Delta t} \mu^{(\text{pulse})}(s) \, ds \\ &= \mu_0(s) - \frac{\omega^{(\text{pulse})} \ln(1 - A^{(\text{pulse})})}{\Delta t} \left( \Phi\left(\frac{t + \Delta t - t^{(\text{pulse})}}{\sigma}\right) - \Phi\left(\frac{t - t^{(\text{pulse})}}{\sigma}\right) \right) \end{aligned} $$

Using the following parameters: $\mu_0 = 0.1$ E/MSY, $\omega = 10^5$, $A^{(\text{pulse})} = 30\%$, $\sigma = 120$ years, and $t^{(\text{pulse})} = 2100$ years AD, we obtain the results given in Figure 5.C.

<figure><img src="image_15.png" /><figcaption>Figure 5.C: Illustration of the Spalding-Hull pulse model</figcaption></figure>
## 1.3 Biodiversity hotspot

A biodiversity hotspot is a region of the world that is both rich in plant and animal species and highly threatened by human activities. Specifically, it is characterized by the following two criteria:

* Exceptional levels of endemism: The region must have at least 1500 species of vascular plants that are endemic, meaning that they are found nowhere else on Earth;

* High levels of habitat loss: The region must have lost at least 70% of its original natural vegetation, typically due to human activities such as deforestation, agriculture, or urbanization.

The term biodiversity hotspot was coined by Norman Myers, who identified 10 geographic regions as conservation priorities (Myers, 1988). This list has been updated twice by Norman Myers: 18 hotspots in 1990 and 25 hotspots in 2000 (Myers, 1990; Myers et al., 2000). New publications have updated this list several times (Mittermeier et al., 2011). The last update is done by Noss et al. (2015), who included the North American Coastal Plain. Today we recognize 36 biodiversity hotspots (Figure 12).

<figure><img src="image_16.png" /><figcaption>Figure 12: The 36 biodiversity hotspots</figcaption></figure>

The 25 original biodiversity hotspots identified by Myers et al. (2000) are in green, while the added eleven regions are in blue. The 36 regions are (1) Tropical Andes, (2) Mesoamerica, (3) Caribbean Islands, (4) Atlantic Forest, (5) Tumbes-Chocó-Magdalena, (6) Cerrado, (7) Chilean Winter Rainfall-Valdivian Forests, (8) California Floristic Province, (9) Madagascar and the Indian Ocean Islands, (10) Coastal Forests of Eastern Africa, (11) Guinean Forests of West Africa, (12) Cape Floristic Region, (13) Succulent Karoo, (14) Mediterranean Basin, (15) Caucasus, (16) Sundaland, Indonesia and Nicobar islands of India, (17) Wallacea of Indonesia, (18) Philippines, (19) Indo-Burma, Bangladesh, India and Myanmar, (20) Mountains of Southwest China, (21) Western Ghats and Sri Lanka, (22) Southwest Australia, (23) New Caledonia, (24) New Zealand, (25) Polynesia-Micronesia, (26) Madrean pine-oak woodlands, (27) Maputaland-Pondoland-Albany, (28) Eastern Afromontane, (29) Horn of Africa, (30) Irano-Anatolian, (31) Mountains of Central Asia, (32) Eastern Himalaya, (33) Japan, (34) East Melanesian Islands, (35) Eastern Australian temperate forests, and (36) North American Coastal Plain.

Source: upload.wikimedia.org/wikipedia/commons/9/93/Biodiversity_Hotspots.svg.
These biodiversity hotspots cover only 2.5% of the Earth's land surface, but support more than half of the world's endemic plant species. As shown in Figure 12, many of these hotspots are concentrated around the tropics. Biodiversity is unevenly distributed across the Earth's surface, a pattern known as the biodiversity gradient. This concept refers to the variation in species diversity across geographic regions, often along specific environmental gradients. The most common example is the latitudinal biodiversity gradient, which describes how species richness generally increases as one moves from the poles toward the equator (Willig et al., 2003). As noted by Gaston and Spicer (2004, Section 3.4, pages 71-85), it is hard to explain this phenomenon<fnref n="28" />, understand the causes and draw general conclusions.

In fact, biodiversity hotspots are often characterized by a high extinction debt because they frequently host species that are on a delayed extinction pathway due to past habitat destruction. These regions are at high risk of losing species in the future, even if no additional habitat loss occurs. The existence of an extinction debt makes conservation efforts in hotspots particularly urgent, as many species may already be committed to extinction. Fragmentation and isolation in these areas exacerbate the problem by weakening the long-term survival chances of species. Therefore, unless immediate action is taken, biodiversity hotspots may face significant hidden biodiversity loss and a substantial extinction debt.

# 2 Ecosystem functions and services

## 2.1 Definition

Ecosystem functions are natural processes, such as nutrient cycling, while ecosystem services are the benefits humans derive from these processes, such as food:

> "In our increasingly technological society, people give little thought to how dependent they are on the proper functioning of ecosystems and the crucial services for humanity that flow from them. Ecosystem services are "the conditions and processes through which natural ecosystems, and the species that make them up, sustain and fulfill human life" (Daily, 1997, page 3); in other words, "the set of ecosystem functions that are useful to humans" (Kremen, 2005, page 468). Although people have been long aware that natural ecosystems help support human societies, the explicit recognition of "ecosystem services" is relatively recent (Mooney and Ehrlich, 1997)." (Sekercioglu, 2010, page 45).

Sekercioglu (2010) classified ecosystem services into 6 categories: (1) climate and biogeochemical cycles (climate stability, air purification, UV protection), (2) regulation of the hydrological cycle (drought mitigation, flood mitigation, water purification), (3) soils and erosion (detoxification and decomposition of wastes, soil formation and soil fertility), (4) biodiversity and ecosystem function (ecosystem goods), (5) mobile linkages (pollination, seed dispersal), and (7) nature's remedies for emerging diseases (medicine, pest control). For his part, Gaston and Spicer (2004, Chapter 4) made

<footnote n="28">²⁸Gaston and Spicer (2004, pages 72 and 73) highlights four key features of the latitudinal biodiversity gradient:</footnote>

<footnote>* Persistence: The latitudinal gradient has been a consistent feature throughout much of Earth's history;</footnote>

<footnote>* Equatorial Peak: The peak of biodiversity often occurs slightly off-center from the equator;</footnote>

<footnote>* Asymmetry: The gradient often shows an asymmetric pattern, with a steeper increase from northern regions toward the equator and a more gradual decrease from the equator to southern regions;</footnote>

<footnote>* Steepness variation: The steepness of the gradient can vary considerably among taxonomic groups. For example, butterflies are more tropical than birds.</footnote>
the distinction between direct-use and indirect-use values of ecosystem services. The direct-use value describes the role of biological resources in consumption or production and mainly concerns commodities such as food, medicine and industrial materials. This category also includes biological control, recreational use (e.g., hunting and fishing), and ecotourism. Indirect-use values are more related to ecosystem functions such as atmospheric regulation, climate regulation, hydrological regulation, nutrient cycling, pest control, pollination, and soil formation and maintenance.

One of the first classifications of ecosystem services was developed by Millennium Ecosystem Assessment (2005, Table 1, page 7 & Box 3.1, page 50). They distinguished 4 families: supporting, provisioning, regulating and cultural services. However, they emphasized the main role of supporting ecosystem services (nutrient cycling, soil formation, primary production), which is essential for the other three ecosystem services<fnref n="29" />. In other words, without supporting ecosystem services, there is no life. The major report of IPBES (2019, Glossary, page 1031) adopted a different classification based on three categories: material (corresponding to provisioning services), regulating (corresponding to the merger of supporting and regulating services), non material (corresponding to cultural services). This three-category system has also been adopted by ENCORE (2024) and TNFD (2023, page 28), which distinguish between (1) provisioning, (2) regulation and maintenance, and (3) cultural services. However, the categorization between the last three systems changes relatively when we consider the Level 2 system<fnref n="30" />. Below is a list of the different ecosystem services described in the 4 classification systems:

1. Aesthetic and cultural services

* Aesthetic, symbolic and spiritual values (nature inspires creativity, provides spiritual connections, and contributes to cultural identity)

* Cultural and spiritual significance (many ecosystems have deep cultural, historical or spiritual significance for local communities and indigenous peoples)

* Educational, scientific and research services (biodiversity provides opportunities for scientific study and learning)

* Recreational opportunities and tourism (forests, parks and other natural areas provide opportunities for recreation and tourism)

* Visual amenity services (non-material benefits that contribute to well-being, emotional satisfaction, and cultural enrichment)

2. Provisioning services

* Energy (natural processes by which ecosystems produce energy such as biomass, solar energy capture, and fossil fuels)

* Food and feed (agriculture, biomass supply, fisheries, plants, animals, seafood, and livestock)

* Genetic resources (biodiversity provides genetic material essential for breeding crops and livestock, and developing new technologies)

<footnote n="29">²⁹Provisioning services include food, freshwater, timber, wood, fiber, fuel, and genetic resources; regulating services include the regulation of climate, floods, disease, water quality, and waste management; and cultural services include recreation, aesthetic enjoyment, education, and spiritual fulfillment.</footnote>

<footnote n="30">³⁰In the case of ENCORE, the classification system is described in the two CSV files of the 2024 zipped database: ENCORE knowledge base/Encore files/02. Ecosystem services definition.csv and ENCORE knowledge base/Encore files/08. Ecosystem services and ecosystem components.csv. A comparison of the three systems (IPBES, ENCORE and TNFD) can be found in NGFS (2024, Table 1, page 45).</footnote>
* Medicinal and biochemical resources (many medicines and pharmaceutical products are derived from natural compounds found in biodiversity)

* Raw materials (timber, fuel wood, minerals, fibers, and other natural resources)

* Water supply (clean water for drinking, irrigation, and industrial use)

### 3. Regulating services

* Air quality regulation (ecosystems filter pollutants from the air, improving air quality)

* Climate regulation (forests absorb carbon dioxide and help regulate global temperatures)

* Waste detoxification and decomposition (natural decomposition of organic matter, natural ability to detoxify harmful chemicals and pollutants)

* Erosion control (vegetation helps stabilize soils, reducing erosion and preventing landslides)

* Hazard and extreme event regulation (flood, storm, rainfall)

* Pest and disease control (natural predators and parasites help regulate populations of harmful organisms)

* Pollination and seed dispersal (bees, birds, insects, and other pollinators allow many plants to reproduce)

* Water purification (freshwater, wetlands, and forests filter pollutants from water)

### 4. Supporting services

* Habitat creation and maintenance (habitats are the natural environments in which organisms live, grow, and reproduce; they form the basis of ecosystems by providing the resources necessary for species to thrive)

* Nutrient cycling (the movement of nutrients through ecosystems, essential for plant growth and productivity)

* Photosynthesis (plants convert solar energy into chemical energy, producing oxygen and forming the base of the food chain)

* Primary production (the production of organic material by plants and algae forms the foundation of ecosystems)

* Soil formation and fertility (the breakdown of rocks and organic matter to create soil)

* Water cycle regulation (ecosystems play an important role in regulating the water cycle, from evaporation to precipitation)

Rather than examining all of these ecosystem services, we focus on two of them (pollination and food) to illustrate the importance of ecosystem functions. We also develop the concept of natural capital, which is essential for valuing these ecosystem services.

## 2.2 Natural capital

Ecosystem services are derived from natural capital, which can be defined as the world's stock of natural assets, including geology, soil, air, water, and all living things. The concept of natural capital in biodiversity is generally attributed to David Pearce, an environmental economist, with his work on the economics of sustainable development (Pearce, 1988). However, the concept itself draws on earlier ideas in ecological economics<fnref n="31" />. For example, the underlying idea of natural capital can be

<footnote n="31">³¹For a historical perspective on natural capital in economics, the reader can refer to Åkerman (2003) and Missemer (2018).</footnote>
found in the extension of input-output models<fnref n="32" /> proposed by Daly (1968), who argued that biology and economics are not two separate sciences but need to be integrated:

> "The purpose of this essay is to bring together some of the more salient similarities between biology and economics and to argue that, far from being superficial, these analogies are profoundly rooted in the fact that the ultimate subject matter of biology and economics is one, viz., the life process." (Daly, 1968, page 392).

However, the concept was really popularized by Robert Costanza in 1997 and his seminal paper on the valuation of ecosystem services and natural capital (Costanza et al., 1997). The definition of natural capital has remained largely consistent since Pearce (1988), for whom natural capital is "the set of all environmental assets". Costanza and Daly (1992) used the stock-flow model to define capital as a stock that provides a flow of valuable goods or services into the future. In this context, natural capital and natural income are simply the stock and flow components, respectively, of natural resources. Today, natural capital is broadly recognized as the stock of environmental assets and ecosystem services that provide goods and services to humans and life. The challenge, once this definition is accepted, is to determine the full extent of these assets and services and to value them accurately.

<table><caption>Table 8: Total value of annual ecosystem services in 1997 (1995 price levels)</caption><thead><tr><th>Biome</th><th>Area (in ha ×10<sup>6</sup>)</th><th>Value (in $/ha/yr)</th><th>Total value (in $bn/yr)</th><th>Breakdown (in %)</th></tr></thead><tbody><tr><td>Marine</td><td>36 302</td><td>577</td><td>20 949</td><td>63.0</td></tr><tr><td>Open ocean</td><td>33 200</td><td>252</td><td>8 381</td><td>25.2</td></tr><tr><td>Coastal</td><td>3 102</td><td>4 052</td><td>12 568</td><td>37.8</td></tr><tr><td>Terrestrial</td><td>15 323</td><td>804</td><td>12 319</td><td>37.0</td></tr><tr><td>Forest</td><td>4 855</td><td>969</td><td>4 706</td><td>14.1</td></tr><tr><td>Grassland & meadow</td><td>3 898</td><td>232</td><td>906</td><td>2.7</td></tr><tr><td>Wetland</td><td>330</td><td>14 785</td><td>4 879</td><td>14.7</td></tr><tr><td>Lake & river</td><td>200</td><td>8 498</td><td>1 700</td><td>5.1</td></tr><tr><td>Desert</td><td>1 925</td><td></td><td></td><td></td></tr><tr><td>Tundra</td><td>743</td><td></td><td></td><td></td></tr><tr><td>Ice & rock</td><td>1 640</td><td></td><td></td><td></td></tr><tr><td>Cropland</td><td>1 400</td><td>92</td><td>128</td><td>0.4</td></tr><tr><td>Urban</td><td>332</td><td></td><td></td><td></td></tr><tr><td>Total</td><td>51 625</td><td></td><td>33 268</td><td>100.0</td></tr></tbody></table>

Source: Costanza et al. (1997, Table 2, page 256) & Author's calculations.

The publication of Costanza et al. (1997) marked a milestone in the valuation of natural capital. They estimated that the value of ecosystem services was in the range of $16–$54 trillion per year, with an average of $33 tn/yr in 1995. Given that world GDP was $28 trillion per year, ecosystems would represent 1.2 times the economic value created by humans (Pearce, 1998). The positive reception of the paper published in Nature was largely supported by the scientific community, although we can find some criticism of the methodology, the total figure of $33 tn/yr and the applicability to environmental policy. However, the impact of the paper has been profound, leading to further research on ecosystem service valuation.

<footnote n="32">³²See Roncalli (2025, Section 8.4.2).</footnote>
The natural capital $\mathcal{K}$ is the sum of the natural capital $\mathcal{K}_{i,j}$ for n biomes and m ecosystem services:

$$ \mathcal{K} = \sum_{i=1}^{n} \sum_{j=1}^{m} \mathcal{K}_{i,j} \qquad (7) $$

We can assume that the value of a biome's ecosystem service is proportional to its area:

$$ \mathcal{K}_{i,j} = A_i V_{i,j} \qquad (8) $$

where $A_i$ is the area of biome i (in hectares) and $V_{i,j}$ is the monetary value of ecosystem service j (in dollars per hectare per year). Therefore, $\mathcal{K}_{i,j}$ and $\mathcal{K}$ are expressed in dollars per year. From Equation (7), we deduce that:

$$ \mathcal{K} = \sum_{i=1}^{n} \mathcal{K}_{i}^{(\text{biome})} = \sum_{j=1}^{m} \mathcal{K}_{j}^{(\text{service})} \qquad (9) $$

where $\mathcal{K}_{i}^{(\text{biome})} = \sum_{j=1}^{m} A_i V_{i,j} = A_i \sum_{j=1}^{m} V_{i,j}$ and $\mathcal{K}_{j}^{(\text{service})} = \sum_{i=1}^{n} A_i V_{i,j}$. To calculate $\mathcal{K}_{i,j}$ or $V_{i,j}$, Costanza et al. (1997) estimated the willingness-to-pay of individuals for ecosystem services. For example, if a 10-hectare forest provides $500 per year in market benefits for raw materials and $250 per year in non-market benefits for aesthetic services, the total value of ecosystem services for that forest would be $750 per year or $75 ha^{-1}yr^{-1}$. In Table 8, we report the values of annual ecosystem services for the different biomes estimated by Costanza et al. (1997). Of the $33 tn, 63\%$ comes from marine biomes and 37% from terrestrial biomes. In the case of marine biomes, both open ocean and coastal areas make a significant contribution, the former because of its large area (33 200 ha), the latter because of its high unit value ($4 052 ha^{-1}yr^{-1}$). In the case of terrestrial biomes, forest and wetland are the two main contributors, the former because of its large area (4 855 ha), the latter because of its high unit value ($14 785 ha^{-1}yr^{-1}$). Table 9 shows the breakdown of the $33 tn$ in terms of the 17 ecosystem services examined by the authors. 51.3% comes from nutrient cycling, followed by cultural services at 9.1%, waste treatment at 6.8%, and disturbance regulation at 5.3%.

The previous study has been updated in 2014 using the same methodology, but with a more comprehensive approach to estimate the unit value $V_{i,j}$. In fact, the unit values in Costanza et al. (2014) are based on the TEEB valuation database developed by Van der Ploeg and de Groot (2010), which collected 1 310 value estimates from 320 publications. An analysis of this database can be found in De Groot et al. (2012), who selected 665 unit values. For example, using 2007 price levels, they estimate that the mean value of coral reefs is $352 249 ha^{-1}yr^{-1}$, while the mean value of open oceans is only $491 ha^{-1}yr^{-1}$. Other interesting figures are: $193 845 ha^{-1}yr^{-1}$ for coastal wetlands, $25 682 ha^{-1}yr^{-1}$ for coastal wetlands, $5 264 ha^{-1}yr^{-1}$ for tropical forests, $4 267 ha^{-1}yr^{-1}$ for lakes and rivers, etc. We report the calculations made by Costanza et al. (2014) for the year 2011 in Table 10. The authors estimated 4 total values of natural capital by considering both 1997 and 2011 figures. Using 2007 price levels<fnref n="33" />, they obtained $45.9 tn/yr$ when considering 2011 biome areas and unit values, $41.6 tn/yr$ when considering 2011 biome areas and 1997 unit values, $145 tn/yr$ when considering 1997 biome areas and 2011 unit values, and $124.8 tn/yr$ when considering 2011 biome areas and unit values. These different figures can be used to assess changes in biome areas and the effect of updated unit values. They concluded that changes in global land use have resulted in a loss of ecosystem services ranging from $4.3 to $20.2 tn/yr.

<footnote n="33">³³The 1997 study used 1995 prices to calculate unit values. To convert them to 2007 prices, we need to multiply them by a factor of 1.38.</footnote>
<table><caption>Table 9: Average global value of annual ecosystem services in 1997 (1995 price levels)</caption><thead><tr><th>#</th><th>Ecosystem service</th><th>Ecosystem functions</th><th>Value (in $ bn/yr)</th><th>Breakdown (in %)</th></tr></thead><tbody><tr><td>1</td><td>Gas regulation</td><td>Regulation of atmospheric chemical composition</td><td>1 341</td><td>4.0</td></tr><tr><td>2</td><td>Climate regulation</td><td>Regulation of global temperature, precipitation, and other biologically mediated climatic processes at global or local levels</td><td>684</td><td>2.1</td></tr><tr><td>3</td><td>Disturbance regulation</td><td>Capacitance, damping, and integrity of ecosystem response to environmental fluctuations</td><td>1 779</td><td>5.3</td></tr><tr><td>4</td><td>Water regulation</td><td>Regulation of hydrological flows</td><td>1 115</td><td>3.4</td></tr><tr><td>5</td><td>Water supply</td><td>Storage and retention of water</td><td>1 692</td><td>5.1</td></tr><tr><td>6</td><td>Erosion control and sediment retention</td><td>Retention of soil within an ecosystem</td><td>576</td><td>1.7</td></tr><tr><td>7</td><td>Soil formation</td><td>Soil formation processes</td><td>53</td><td>0.2</td></tr><tr><td>8</td><td>Nutrient cycling</td><td>Storage, internal cycling, processing, and acquisition of nutrients</td><td>17 075</td><td>51.3</td></tr><tr><td>9</td><td>Waste treatment</td><td>Recovery of mobile nutrients and removal or breakdown of excess or xenic nutrients and compounds</td><td>2 277</td><td>6.8</td></tr><tr><td>10</td><td>Pollination</td><td>Movement of floral gametes</td><td>117</td><td>0.4</td></tr><tr><td>11</td><td>Biological control</td><td>Trophic-dynamic regulations of populations</td><td>417</td><td>1.3</td></tr><tr><td>12</td><td>Refugia</td><td>Habitat for resident and transient populations</td><td>124</td><td>0.4</td></tr><tr><td>13</td><td>Food production</td><td>That portion of gross primary production extractable as food</td><td>1 386</td><td>4.2</td></tr><tr><td>14</td><td>Raw materials</td><td>That portion of gross primary production extractable as raw materials</td><td>721</td><td>2.2</td></tr><tr><td>15</td><td>Genetic resources</td><td>Sources of unique biological materials and products</td><td>79</td><td>0.2</td></tr><tr><td>16</td><td>Recreation</td><td>Providing opportunities for recreational activities</td><td>815</td><td>2.4</td></tr><tr><td>17</td><td>Cultural</td><td>Providing opportunities for non-commercial uses</td><td>3 015</td><td>9.1</td></tr></tbody><tfoot><tr><td></td><td>Total</td><td></td><td>33 268</td><td>100.0</td></tr></tfoot></table>

Source: Costanza et al. (1997, Table 2, page 256) & Author's calculations.
<table><caption>Table 10: Changes in annual ecosystem services between 1997 and 2011</caption><thead><tr><th rowspan="2"></th><th colspan="2">Area<br>(in hectare)</th><th colspan="2">Unit values<br>(in $/ha/yr)</th><th colspan="4">Total value<br>(in $/yr)</th></tr><tr><th>1997</th><th>2011</th><th>2007</th><th>2007</th><th>1995</th><th>2007</th><th>2007</th><th>2007</th></tr></thead><tbody><tr><td>Price levels</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Area</td><td>1997</td><td>2011</td><td></td><td></td><td>1997</td><td>1997</td><td>2011</td><td>1997</td></tr><tr><td>Unit values</td><td></td><td></td><td>1997</td><td>2011</td><td>1997</td><td>1997</td><td>1997</td><td>2011</td></tr><tr><td>Marine</td><td>36 302</td><td>36 302</td><td>796</td><td>1 368</td><td>20.9</td><td>28.9</td><td>29.5</td><td>60.5</td></tr><tr><td>Open Ocean</td><td>33 200</td><td>33 200</td><td>348</td><td>660</td><td>8.4</td><td>11.6</td><td>11.6</td><td>21.9</td></tr><tr><td>Coastal</td><td>3 102</td><td>3 102</td><td>5 592</td><td>8 944</td><td>12.6</td><td>17.3</td><td>18.0</td><td>38.6</td></tr><tr><td>Terrestrial</td><td>15 323</td><td>15 323</td><td>1 109</td><td>4 901</td><td>12.3</td><td>17.0</td><td>12.1</td><td>84.5</td></tr><tr><td>Forest</td><td>4 855</td><td>4 261</td><td>1 338</td><td>3 800</td><td>4.7</td><td>6.5</td><td>4.7</td><td>19.5</td></tr><tr><td>Grassland</td><td>3 898</td><td>4 418</td><td>321</td><td>4 166</td><td>0.9</td><td>1.2</td><td>1.4</td><td>16.2</td></tr><tr><td>Wetland</td><td>330</td><td>188</td><td>20 404</td><td>140 174</td><td>4.9</td><td>6.7</td><td>3.4</td><td>36.2</td></tr><tr><td>Lake & river</td><td>200</td><td>200</td><td>11 727</td><td>12 512</td><td>1.7</td><td>2.3</td><td>2.3</td><td>2.5</td></tr><tr><td>Cropland</td><td>1 400</td><td>1 672</td><td>126</td><td>5 567</td><td>0.1</td><td>0.2</td><td>0.2</td><td>7.8</td></tr><tr><td>Urban</td><td>332</td><td>352</td><td></td><td>6 661</td><td></td><td></td><td></td><td>2.2</td></tr><tr><td>Total</td><td>51 625</td><td>51 625</td><td></td><td></td><td>33.3</td><td>45.9</td><td>41.6</td><td>145.0</td></tr><tr><td>Difference</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-4.3</td><td>-20.2</td></tr></tbody></table>

Source: Costanza et al. (2014, Table 3, page 156) & Author's calculations.

<figure><img src="image_17.png" /><figcaption>Figure 13: World map with the different ecosystem types and the calculated values of their ecosystem services (in US dollars per hectare per year)</figcaption></figure>

Source: World Ocean Review (2015, Figure 1.12, page 27).
**Remark 4** Since 1997, the valuation of ecosystem services has been widely adopted by scientists, organizations and policy makers<fnref n="34" /> (Hein et al., 2020; Legesse et al., 2022). The following are some of the frameworks, projects and initiatives for the valuation of ecosystem services<fnref n="35" />: System of Environmental-Economic Accounting (SEEA), Common International Classification of Ecosystem Services (CICES), The Economics of Ecosystems and Biodiversity (TEEB), Natural Capital Accounting and Valuation of Ecosystem Services (NCAVES).

Box 5: The System of Environmental-Economic Accounting (SEEA)

The System of Environmental-Economic Accounting (SEEA), endorsed by the United Nations, is a framework that integrates economic and environmental data to provide a comprehensive view of the interactions between the economy and the environment, and the stocks and flows of environmental assets. It establishes common concepts, definitions, classifications, and accounting rules, to enable the production of internationally comparable statistics and accounts. The SEEA framework follows an accounting structure similar to the System of National Accounts (SNA), ensuring coherence with traditional economic accounting practices. The SEEA is modular, with each module addressing a specific topic. The SEEA central framework develops the rules and guidelines for measuring the relationship between the environment and the economy, focusing on three key areas: environmental flows (changes in natural assets), stocks of environmental assets (measurement of natural assets) and economic activity related to the environment (monetary economic flows related to natural assets). The four main modules are:

* Ecosystem accounting (SEEA EA) with 4 types of accounts: ecosystem extent accounts, ecosystem condition accounts, ecosystem services flow accounts (physical and monetary), and monetary ecosystem asset accounts;

* Agriculture, forestry and fisheries with two types of accounts: flow accounts and asset accounts (both physical and monetary);

* SEEA-Energy with two types of accounts: flow accounts and asset accounts (both physical and monetary);

* SEEA-Water with three types of accounts: physical flow accounts, physical asset accounts and economic accounts.

In addition, four other modules have been developed on air emissions, environmental activities, land and material flow accounts. Examples of SEEA accounts can be found at seea.un.org/content/projects.

In January 2020, the World Economic Forum published a series of reports aimed at “providing pathways for business to be part of the transition to a nature-positive economy”. In particular, World Economic Forum (2020a) estimated that $44 trillion of economic value creation — more than half of global GDP — is moderately or highly dependent on nature<fnref n="36" />. Among the 163 economic

<footnote n="34">³⁴World maps of ecosystem valuation, such as Figure 13, are very common in academic and policy publications.</footnote>

<footnote n="35">³⁵The corresponding websites are seea.un.org, www.cices.eu, www.teebweb.org, and seea.un.org/home/natural-capital-accounting-project.</footnote>

<footnote n="36">³⁶The exact figures are $31 tn or 37% of the world GDP for moderately dependent industries and $13 tn or 15% of the world GDP for highly dependent industries.</footnote>
sectors considered in the study, construction ($4 tn$), agriculture ($2.5 tn$), and food and beverages ($1.4 tn$) are the three largest industries most dependent on nature. The impact on secondary and tertiary sectors can also be significant through their supply chains. This publication was followed by several public studies in 2021 showing how GDP creation is strongly linked to biodiversity<fnref n="37" />. These reports consistently highlight that the link between GDP and biodiversity is currently poorly understood, while the economic and financial risks posed by biodiversity loss are enormous.

## 2.3 Pollination service

Pollination is the process by which pollen is transferred from the male part of a flower (the anther) to the female part (the stigma) of the same or another flower. This is a crucial step in the reproductive cycle of many plants, as it leads to the production of seeds and fruits. There are two main types of pollination:

1. Self-pollination, in which pollen from one flower is transferred to the stigma of the same flower. For example, many crops and fruit trees are self-pollinating, including aubergines, barley, beans, cauliflower, lentils, lettuce, olives, onions, peppers, potatoes, soybeans, tomatoes, rice, and wheat;

2. Cross-pollination, when pollen is transferred from the anther of one flower to the stigma of a flower on another plant of the same species. Examples include apples, blackberries, black-currants, broccoli, carrots, cacao, daffodils, lavender, pears, plums, pumpkins, raspberries, strawberries, and tulips.

We also distinguish three methods of cross-pollination:

1. Abiotic pollination involves natural transport phenomena such as wind, water, and rain. Examples of wind-pollinated plants include conifers, grasses, and many trees.

2. Biotic pollination requires living pollinators to move pollen from one flower to another. Most pollinators are insects (ants, beetles, bees, butterflies, flies, wasps and moths), but some are vertebrates (bats, birds, e.g., honeyeaters and hummingbirds).

3. Hand pollination (also known as mechanical or human pollination) is a technique in which humans manually transfer pollen from the male to the female plant. Examples of plants that are commonly hand pollinated include corn, cucumbers, melons, vanilla, and zucchini.

These classifications are only theoretical. Most plants are pollinated in more than one way. For example, a self-pollinating species may also be pollinated by animals or by hand. Similarly, 100% of apples are not 100% animal pollinated. Olhnuud et al. (2022) showed that the animal-dependent pollination rate varies from species to species (e.g., Gala vs. Golden apple) and from region to region (e.g., Asia vs. Europe).

By analyzing data of 137 single crops and 115 commodity<fnref n="38" /> crops provided by FAO, Klein et al. (2007) identified 124 major crops (57 single crops and 67 commodity crops) used for human food with significant annual production, representing 99% of total world food production. They

<footnote n="37">³⁷We can cite Dasgupta (2021), OECD (2021) and Svartzman et al. (2021) among others.</footnote>

<footnote n="38">³⁸A single crop refers to a specific plant species. A commodity, on the other hand, represents a group of different crop species. For instance, the fresh vegetables category as defined by the FAO includes 21 distinct crops, such as celery and rhubarb. Similarly, other commodity categories include fresh fruits (15 crops, including litchi and pawpaw), fresh tropical fruits (17 crops, including guava and passion fruit), roots and tubers (8 crops, such as yam bean and topinambur), and pulses (6 crops, including guar bean and velvet bean).</footnote>
Box 6: The story of the original vanilla bean

The Chinantla Forest is considered the birthplace of vanilla, and the vanilla plant, or vine, is native to Mexico. There, the vines grew and flourished without the help of humans. Wild vanilla is naturally pollinated by melipona bees and small hummingbirds found only in Mexico. Before 1850, all vanilla beans came from the forests of Mexico, and France was the number one importer of the ‘black flower’. The Aztecs, and the Mayans before them, believed that the scent of vanilla could help them communicate with the gods and had long mastered the fermentation techniques needed to cure the beans. They cultivated ‘tlilxochitl’ or black flowers so that the flavors could be combined with cocoa and coffee. In 1521, Cortés was the first European to bring the dark pods or beans back to Charles Quint. Vanilla beans first arrived in France in 1664. Later, Louis XIV fell in love with the taste of vanilla and wanted vanilla beans to be grown on the island of Réunion, then known as Bourbon Island. But until the mid-19th century, vanilla beans were still only made in Mexico. Although the technique of curing the beans was known, pollination of the flower was not. In 1836 and 1841, Charles Morren, a Belgian botanist, and Edmond Albius, a slave on Réunion Island discovered how to bypass bee pollination by manually pollinating vanilla flowers. Soon after, vanilla plants were exported by the French to plantations in Tahiti, Madagascar, Mauritius, Réunion Island, and the Comoros.

Text reproduced from www.epices-roellinger.com.

estimated that 70% of these major crops depend on animal pollination (87 crops), 23% do not rely on animal pollination (28 crops), while 7% have not been evaluated (9 crops). Despite this, in terms of global production in 2004, these three categories contributed 35%, 60%, and 5%, respectively. This is because the four largest crops (sugar cane, corn, wheat, and rice) do not require animal pollination, but represented more than 50% of global crop production in 2004. Klein et al. (2007) also created a classification of the pollination dependence of different crops. They considered a crop to be pollinator dependent if animal pollination is required to increase the quantity and/or quality of fruits or seeds directly consumed by humans. Alternatively, a crop is considered non-dependent if it is pollinated either abiotically (wind) or autogamously (self-fertilizing). They created five categories:

1. Essential
Animal pollinators are essential for most varieties, otherwise we observe a reduction in production of more than 90%, comparing experiments with and without animal pollinators;

2. High
Animal pollinators are strongly needed (40 to less than 90% reduction);

3. Modest
Animal pollinators are clearly beneficial (10 to less than 40% reduction);

4. Little
Some evidence suggests that animal pollinators are beneficial (greater than 0 to less than 10% reduction);

5. No increase
No increase in production with animal pollination.

Table 11 shows the classification found by Klein et al. (2007, Supplemental Material 2) (103 crops) and updated by Aizen et al. (2019, Appendix S1) (11 additional crops).
<table><caption>Table 11: How dependent are foods on pollinator insects?</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>No dependency</td><td>Yields are not affected by pollinators<br><img src="" alt="Wheat icon"> Cereals: barley, maize, millet, oats, rice, rye, sorghum, wheat<br><img src="" alt="Carrot icon"> Roots and tubers: carrots, cassava, potatoes, sweet potatoes<br><img src="" alt="Peas icon"> Legumes including chickpeas, lentils, peas<br><img src="" alt="Banana icon"> Fruit and veg including bananas, grapes, lettuce, pepper, pineapples<br><img src="" alt="Pineapple icon"> Sugar crops: sugar beet, sugar cane<br><img src="" alt="Broccoli icon"> Also includes areca nuts, asparagus, broccoli, cabbages, castor oil seed, cauliflower, chicory roots, dates, garlic, hazelnuts, jojoba seeds, leeks, olives, onions, pistachios, quinoa, spinach, taro, triticale, walnuts, yams</td></tr><tr><td>Little dependency</td><td>Yield reduction of 0% to 10% without pollinators<br><img src="" alt="Orange icon"> Fruits and veg including lemons, limes, oranges, papayas, tomatoes<br><img src="" alt="Palm icon"> Oilcrops including linseed, palm oil, poppy seed, safflower seed<br><img src="" alt="Cassava icon"> Legumes including beans (dry & green), cow peas, pigeon peas<br><img src="" alt="Pigeon icon"> Groundnuts<br><img src="" alt="Grape icon"> Also includes bambara beans, chillies, clementines, grapefruit, mandarins, persimmons, string beans, tangerines</td></tr><tr><td>Modest dependency</td><td>Yield reduction of 10% to 40% without pollinators<br><img src="" alt="Sunflower icon"> Oilcrops including mustard seed, rapeseed, sesame, sunflower seed<br><img src="" alt="Soybean icon"> Soybeans<br><img src="" alt="Strawberry icon"> Fruits including currants, eggplant, figs, gooseberries, strawberries<br><img src="" alt="Coconut icon"> Coconuts and okra<br><img src="" alt="Coffee icon"> Coffee beans<br><img src="" alt="Chestnut icon"> Also includes broad beans, chestnut, karite nuts, seed cotton</td></tr><tr><td>High dependency</td><td>Yield reduction of 40% to 90% without pollinators<br><img src="" alt="Apple icon"> Fruits including apples, apricots, blueberries, cherries, cranberries, guavas, mangoes, nectarines, peaches, plums, pears, raspberries<br><img src="" alt="Almond icon"> Nuts including almonds, cashew nuts, kola nuts<br><img src="" alt="Avocado icon"> Avocados<br><img src="" alt="Cucumber icon"> Also includes anise, badian, buckwheat, coriander, cucumber, fennel, nutmeg</td></tr><tr><td>Essential</td><td>Yield reduction greater than 90% without pollinators<br><img src="" alt="Kiwi icon"> Fruits including kiwi, melons, pumpkins, watermelons<br><img src="" alt="Cocoa icon"> Cocoa beans<br><img src="" alt="Brazil nut icon"> Brazil nuts<br><img src="" alt="Vanilla icon"> Also includes quinces, vanilla</td></tr></tbody></table>

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

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<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

<figure><img src="image_35.png" /></figure>

<figure><img src="image_36.png" /></figure>

<figure><img src="image_37.png" /></figure>

<figure><img src="image_38.png" /></figure>

<figure><img src="image_39.png" /></figure>

<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /></figure>

<figure><img src="image_42.png" /></figure>

Source: Klein et al. (2007, Supplemental Material 2), Aizen et al. (2019, Appendix S1), https://ourworldindata.org/pollinator-dependence & icons taken from https://icons8.comicons.
Box 7: Who are animal pollinators?

Bees are the most important group of animal pollinators. There are an estimated 20 000 species of bees (family Apidae), but only nine species of honey bees are recognized and form the genus Apis (Apidae; Apinae; Apini; Apis). The Western honey bee (Apis mellifera) is the most common honey bee and the one most often domesticated for honey production. The other species are Apis andreniformis, Apis cerana (Asiatic honey bee), Apis dorsata (Giant honey bee), Apis florea (Little honey bee), Apis koschevnikovi, Apis laboriosa (Himalayan honey bee), Apis nigrocincta and Apis nuluensis. We generally distinguish between honey bees that are managed by humans and wild bees. There are many species in the latter category, but the most important are Bumble bees (Apidae; Apinae; Bombini), Carpenter bees (Apidae; Xylocopinae), Stingless bees (Apidae; Apinae; Meliponini), and solitary bees such as sand bees (family Andrenidae; Andreninae; Andrena) or nomad bees (Apidae; Nomadinae; Nomadini; Nomada). Bees are generally attracted to yellow (and blue) flowers.

Non-bee insects also play a significant role in global crop pollination. For instance, Rader *et al.* (2016) found that approximately 40% of visits to crop flowers are made by non-bee insects. In fact, butterflies and moths (order Lepidoptera) are the second most important group of animal pollinators. Other insects that contribute to pollination include ants (family Formicidae), beetles (order Coleoptera), and flies (order Diptera). In the case of ants, pollination typically occurs in low-growing flowers positioned close to the stem. Examples of ant-pollinated plants include small's stonecrop (Diamorpha smallii), alpine nailwort (Paronychia pulvinata), and cascade knotweed (Polygonum cascadense). Butterflies have excellent color vision, which explains why they are attracted to red, orange, yellow, blue and purple flowers. Moths, on the other hand, prefer pale or white flowers because they tend to come out at night.

The primary pollinators of cacao are tiny flies from the families of biting midges (Ceratopogonidae, including the genus *Forcipomyia*) and, to a lesser extent, gall midges (Cecidomyiidae). These small flies, sometimes only a few millimeters long, are uniquely suited to pollinate cacao because the reproductive parts of cacao flowers are very small (less than 2 mm) and complex, with structures that make them difficult for larger insects to access.
In addition to insect pollinators, vertebrate pollinators also participate in the reproductive success of plants, especially tropical plants (Ratto *et al.*, 2018). Bird pollinators include hummingbirds (Trochilidae), sunbirds (Nectariniidae), honeycreepers (Meliphagidae), and some parrots. Birds are generally attracted to red, orange, and yellow flowers. Some known bird-pollinated plants include hibiscus, eucalyptus, and some orchids. Bats, like moths, prefer pale or white flowers. They are involved in the pollination of mango, banana, durian, guava, and agave (used to make tequila). While rodents and reptiles are less common vertebrate pollinators, they can still contribute to the reproduction of certain plants.

It is very difficult to estimate the contribution of each species to pollination. However, it is generally accepted that managed honey bees provide 50-75% of agricultural pollination, while wild bees and other pollinators account for the remaining 25-50% (Garibaldi *et al.*, 2013; IPBES, 2016).
Using the previous classification, Aizen et al. (2009) estimated that the direct reduction in total agricultural production in the absence of animal pollination would be 5% for developed regions and 8% for developing regions. These figures are based on the production deficit in volume, calculated as:

$$D_t^{(\text{volume})} = \frac{\sum_{i=1}^{n} P_{i,t} - \sum_{i=1}^{n} P_{i,t} (1 - \delta_i)}{\sum_{i=1}^{n} P_{i,t}} = \frac{\sum_{i=1}^{n} P_{i,t} \delta_i}{\sum_{i=1}^{n} P_{i,t}} = \sum_{i=1}^{n} w_{i,t} \delta_i \quad (10)$$

where n is the number of crops, $P_{i,t}$ is the volume production in metric tonnes of crop i in year t, $w_{i,t}$ is the weight of crop i in the total agricultural production, $\delta_i$ is the dependency rate, which is equal to 0% for crops that are not dependent on animal pollinators and 100% for crops that are completely dependent on animal pollinators<fnref n="39" />. Aizen et al. (2009) also calculated the percentage increase in area needed to compensate for the production deficit:

$$A_t^{(\text{compensation})} = \frac{\sum_{i=1}^{n} \frac{A_{i,t}}{1 - \delta_i} - \sum_{i=1}^{n} A_{i,t}}{\sum_{i=1}^{n} A_{i,t}} = \frac{\sum_{i=1}^{n} A_{i,t} \frac{\delta_i}{1 - \delta_i}}{\sum_{i=1}^{n} A_{i,t}} = \sum_{i=1}^{n} w_{i,t} \frac{\delta_i}{1 - \delta_i} \quad (11)$$

where $A_{i,t}$ is the cultivated area (in hectares) of crop i in year t and $(1 - \delta_i)^{-1} A_{i,t}$ is the area needed to produce $P_{i,t}$ in the absence of pollination<fnref n="40" />. They found that area compensation is 15% in developed regions and 42% in developing regions. Another interesting finding is that production deficit and area compensation have generally increased over time. These different results are mainly explained by the fact that human diets have changed over time and that human diets today are more diversified than fifty years ago, with more vegetables and fruits being consumed. In addition, the low figures for production deficit are mainly due to the importance of cereals in the human diet, while the high figures for area compensation are mainly due to the greater area needed to cultivate crops that depend on animal pollination, e.g., apples, avocados, cocoa, mangoes, peaches. In terms of volume and metric tonnes, the production yield of the first category is higher than that of the second. However, it's worth considering whether a volume-based analysis is the most appropriate approach to assess the importance of pollinators. For example, 1 kg of wheat and 1 kg of tomatoes provide different nutritional values, suggesting that volume alone may not accurately reflect their contribution to human well-being. Eilers et al. (2011) conducted a similar analysis using the same data and methodology but focused on the nutritional value of crops instead of volume. Let $V_{j,t}^{(\text{nutritional})}$ be the total amount of nutrient j in year t. We have:

$$V_{j,t}^{(\text{nutritional})} = \sum_{i=1}^{n} V_{i,j}^{(\text{nutritional})} P_{i,t} (1 - R_i) \quad (12)$$

where $V_{i,j}^{(\text{nutritional})}$ is the amount of nutrient j in a metric tonne of crop i, $P_{i,t}$ is the volume production in tonnes of crop i in year t, and $R_i$ is the proportion of crop i that is not consumed by humans due to inedible parts, such as pits, stems, or shells. We can decompose $V_{j,t}^{(\text{nutritional})}$ into three components: $V_{j,t}^{(1)} = \sum_{i=1}^{n} 1 \{\delta_i = 0\} \cdot V_{i,j}^{(\text{nutritional})} P_{i,t} (1 - R_i)$ is the nutritional value of pollinator-independent crops; $V_{j,t}^{(2)} = \sum_{i=1}^{n} 1 \{\delta_i > 0\} \cdot (1 - \delta_i) V_{i,j}^{(\text{nutritional})} P_{i,t} (1 - R_i)$ is the nutritional value of pollinator-dependent crops due to abiotic and self-pollination; $V_{j,t}^{(3)} = \sum_{i=1}^{n} 1 \{\delta_i > 0\} \cdot \delta_i V_{i,j}^{(\text{nutritional})} P_{i,t} (1 - R_i)$ is the nutritional value of pollinator-dependent crops attributed to animal pollination alone. Results are shown in Table 12, where the key metric to consider

<footnote n="39">³⁹Aizen et al. (2009) used the following values for $\delta_i$: 0%, 5%, 25%, 65% and 95% for no, little, modest, high and essential dependency classes.</footnote>

<footnote n="40">⁴⁰We assume that production is proportional to area: $P_{i,t} \propto A_{i,t}$.</footnote>
is $V_{j,t}^{(3)}$ (last column). In terms of energy (calories) and protein, about 80% of the human diet comes from pollinator-independent crop production. The proportion attributed to crop production dependent on animal pollination is low, at less than 3%. Similar figures are observed for minerals, except for fluoride and calcium, where the proportions attributed to animal pollination are 19.83% and 9.11%, respectively. The most significant effects of animal pollination are observed for vitamins<sup>41</sup>, especially vitamin A (41.03%), carotene (about 40%), certain forms of vitamin E (about 20%) and vitamin C (19.64%). We conclude that animal pollination has a significant impact on human diets by contributing to nutritional diversification, particularly at the vitamin level.

<table><caption>Table 12: Proportion in % of nutrients derived from pollinator-independent and pollinator-dependent crops</caption><thead><tr><th>Nutrient</th><th></th><th>V<sub>j,t</sub><sup>(1)</sup></th><th>V<sub>j,t</sub><sup>(2)</sup></th><th>V<sub>j,t</sub><sup>(3)</sup></th></tr></thead><tbody><tr><td rowspan="3">Macro-nutrients</td><td>Energy</td><td>78.83</td><td>18.59</td><td>2.58</td></tr><tr><td>Protein</td><td>83.43</td><td>13.57</td><td>3.00</td></tr><tr><td>Fat</td><td>26.02</td><td>66.98</td><td>7.00</td></tr><tr><td rowspan="16">Vitamins</td><td>A</td><td>28.71</td><td>30.26</td><td>41.03</td></tr><tr><td>β-carotene</td><td>27.44</td><td>34.19</td><td>38.37</td></tr><tr><td>α-carotene</td><td>32.25</td><td>29.83</td><td>37.92</td></tr><tr><td>β-cryptoxanthin (carotene)</td><td>0.77</td><td>56.99</td><td>42.24</td></tr><tr><td>Lycopene (carotene)</td><td>0.00</td><td>56.67</td><td>43.33</td></tr><tr><td>Lutein & Zeaxanthin (carotene)</td><td>94.05</td><td>3.92</td><td>2.03</td></tr><tr><td>E (α-tocopherol)</td><td>63.73</td><td>28.94</td><td>7.33</td></tr><tr><td>E (β-tocopherol)</td><td>0.63</td><td>72.50</td><td>26.87</td></tr><tr><td>E (γ-tocopherol)</td><td>32.92</td><td>52.66</td><td>14.42</td></tr><tr><td>E (δ-tocopherol)</td><td>14.87</td><td>62.50</td><td>22.63</td></tr><tr><td>K</td><td>71.55</td><td>19.28</td><td>9.17</td></tr><tr><td>C</td><td>6.99</td><td>73.37</td><td>19.64</td></tr><tr><td>B1 (Thiamin)</td><td>95.29</td><td>4.00</td><td>0.71</td></tr><tr><td>B2 (Riboflavin)</td><td>97.66</td><td>1.92</td><td>0.42</td></tr><tr><td>B3 (Niacin)</td><td>89.46</td><td>8.93</td><td>1.61</td></tr><tr><td>B5 (Pantothenic acid)</td><td>87.57</td><td>9.34</td><td>3.09</td></tr><tr><td>B6</td><td>97.93</td><td>1.58</td><td>0.49</td></tr><tr><td>B9 (Folate)</td><td>55.49</td><td>37.19</td><td>7.32</td></tr><tr><td rowspan="11">Minerals</td><td>Calcium</td><td>42.40</td><td>48.49</td><td>9.11</td></tr><tr><td>Iron</td><td>70.66</td><td>23.14</td><td>6.20</td></tr><tr><td>Magnesium</td><td>88.50</td><td>9.06</td><td>2.44</td></tr><tr><td>Phosphorus</td><td>89.06</td><td>8.72</td><td>2.22</td></tr><tr><td>Potassium</td><td>72.74</td><td>20.93</td><td>6.33</td></tr><tr><td>Sodium</td><td>87.18</td><td>8.63</td><td>4.19</td></tr><tr><td>Zinc</td><td>91.80</td><td>6.54</td><td>1.66</td></tr><tr><td>Copper</td><td>80.92</td><td>15.21</td><td>3.87</td></tr><tr><td>Manganese</td><td>93.87</td><td>4.94</td><td>1.19</td></tr><tr><td>Selenium</td><td>97.46</td><td>1.97</td><td>0.57</td></tr><tr><td>Fluoride</td><td>45.57</td><td>34.60</td><td>19.83</td></tr></tbody></table>

Source: Eilers et al. (2011, Table 1, page 2011).

<footnote n="41"><sup>41</sup>Vitamin A is essential for vision, vitamin C is a powerful antioxidant and vital for collagen production, vitamin E plays a role in immune function, and carotenes act as precursors to vitamin A.</footnote>
Another interesting figure is that 308 000 out of a total of 352 000 flowering plants are partially or totally pollinated by animals, which represents a proportion of 87.5% (Ollerton et al., 2011). These species, known as angiosperms (*Angiospermae*), include many fruit trees and flowers such as roses and tulips. While the primary benefits of these species are food and medicine, they also provide secondary benefits such as reducing pest populations and improving soil and water quality. Another important service is the enhancement of rural aesthetics and the provision of cultural and visual amenities (Wratten et al., 2012; Dicks et al., 2021). Without bees and butterflies, the world would not be the same, and many blue, orange, pink, purple, red, violet and yellow flowers would disappear, as these pollinators are essential for their reproduction. The loss of these vibrant flowers would have a significant impact on the beauty of natural landscapes.

<figure><img src="image_43.png" /><figcaption>Figure 14: Trend in the number of bee colonies (1961–2022)</figcaption></figure>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.

Potts et al. (2010) alerted the scientific community and policy makers to the global decline of pollinators and its potential impact on human well-being:

> "Pollinators are a key component of global biodiversity, providing vital ecosystem services to crops and wild plants. There is clear evidence of recent declines in both wild and domesticated pollinators, and parallel declines in the plants that rely upon them." (Potts et al., 2010, page 345).

It is challenging to accurately define pollinator decline, as data can sometimes initially be contradictory. For example, Potts et al. (2010) reported declines in honey bee populations in the United States (59% loss of colonies between 1947 and 2005) and Central Europe (25% loss of colonies between 1985 and 2005). Globally, however, the number of managed honey bee colonies has increased over the past six decades. From 1965 to 2015, production of pollinator-dependent crops has increased by 300% (IPBES, 2016, page XXI). This increase is mainly due to the growing presence
<table><caption>Table 13: Regional distribution of managed honey bee colonies (in millions)</caption><thead><tr><th rowspan="2">Region</th><th colspan="4">Stock (in million colonies)</th><th colspan="2">Growth (in %)</th></tr><tr><th>1961</th><th>1980</th><th>2000</th><th>2022</th><th>1961-2022</th><th>2000-2022</th></tr></thead><tbody><tr><td>Europe</td><td>21.10</td><td>21.42</td><td>15.55</td><td>25.12</td><td>19.1</td><td>61.6</td></tr><tr><td>Western Europe</td><td>3.76</td><td>3.35</td><td>2.45</td><td>3.55</td><td>-5.5</td><td>45.3</td></tr><tr><td>Northern Europe</td><td>0.44</td><td>0.40</td><td>0.27</td><td>0.64</td><td>45.6</td><td>138.3</td></tr><tr><td>Eastern Europe</td><td>14.02</td><td>13.71</td><td>7.36</td><td>10.66</td><td>-24.0</td><td>44.8</td></tr><tr><td>Southern Europe</td><td>2.87</td><td>3.95</td><td>5.47</td><td>10.27</td><td>257.3</td><td>87.6</td></tr><tr><td>Americas</td><td>10.02</td><td>10.03</td><td>10.62</td><td>11.71</td><td>16.9</td><td>10.2</td></tr><tr><td>Northern America</td><td>5.85</td><td>4.75</td><td>3.22</td><td>3.40</td><td>-41.9</td><td>5.5</td></tr><tr><td>Central America</td><td>2.26</td><td>2.80</td><td>2.19</td><td>2.68</td><td>18.5</td><td>22.3</td></tr><tr><td>Caribbean</td><td>0.23</td><td>0.32</td><td>0.28</td><td>0.40</td><td>72.5</td><td>45.8</td></tr><tr><td>South America</td><td>1.67</td><td>2.16</td><td>4.94</td><td>5.23</td><td>212.4</td><td>6.0</td></tr><tr><td>Africa</td><td>6.85</td><td>9.37</td><td>15.92</td><td>17.46</td><td>155.1</td><td>9.7</td></tr><tr><td>Asia</td><td>10.70</td><td>18.61</td><td>26.82</td><td>45.34</td><td>323.6</td><td>69.1</td></tr><tr><td>Oceania</td><td>0.51</td><td>0.76</td><td>0.80</td><td>1.36</td><td>168.7</td><td>70.9</td></tr><tr><td>World</td><td>49.17</td><td>60.20</td><td>69.71</td><td>101.00</td><td>105.4</td><td>44.9</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.

of fruits in human diets (such as tropical and seasonal fruits). However, many pollinator species are listed as vulnerable, endangered or critically endangered on the IUCN Red List. In fact, we need to distinguish between managed honey bees and other animal pollinators. According to FAO statistics<sup>42</sup>, the number of managed bee colonies has doubled between 1961 and 2022 (Figure 14). In 1961, there were 49.2 million colonies, while today there are more than 100 million (Table 13). Most of this growth has occurred in Asia (+324%), Africa (+155%), Southern Europe (+257%) and South America (+212%). Below is a regional breakdown of colony numbers:

<table><thead><tr><th>Year</th><th>Europe</th><th>America</th><th>Africa</th><th>Asia</th><th>Oceania</th></tr></thead><tbody><tr><td>1961</td><td>42.9%</td><td>20.4%</td><td>13.9%</td><td>21.8%</td><td>1.0%</td></tr><tr><td>2022</td><td>24.9%</td><td>11.6%</td><td>17.3%</td><td>44.9%</td><td>1.3%</td></tr></tbody></table>

Asia now accounts for 45% of the global market, followed by Europe with 25%. Three regions have experienced a decline in honey bee populations over the last sixty years: North America (−41.9%), Eastern Europe (−24.0%), and Western Europe (−5.5%). However, in the past 20 years, they have reversed this trend, showing positive growth. The current problem is not the decline of honey bee colonies, but the dramatic decline of insects worldwide. For example, Hallmann et al. (2017) measured a decline in total flying insect biomass of more than 75 percent over 27 years in 63 German protected areas. Sánchez-Bayo and Wyckhuys (2019) estimate that 40% of the world's insect species could become extinct in the next few decades. The case of butterflies, for example, is dramatic, as shown by Warren et al. (2021), who studied the status of butterflies in the United Kingdom, the Netherlands, and Belgium:

> "[...] In the United Kingdom, 8% of resident species have become extinct, and since 1976 overall numbers declined by around 50%. In the Netherlands, 20% of species have become extinct, and since 1990 overall numbers in the country declined by 50%. Distribution

<footnote n="42"><sup>42</sup>The data can be obtained from the FAO website: www.fao.org/faostat/en/#data/QCL. Select the domain *Crops and livestock products*, then the item *Live Animals/Bees* and the element *Stocks*.</footnote>
trends showed that butterfly distributions began decreasing long ago, and between 1890 and 1940, distributions declined by 80%. In Flanders (Belgium), 20 butterflies have become extinct (29%), and between 1992 and 2007 overall numbers declined by around 30%. A European Grassland Butterfly Indicator from 16 European countries shows there has been a 39% decline of grassland butterflies since 1990. The 2010 Red List of European butterflies listed 38 of the 482 European species (8%) as threatened and 44 species (10%) as near threatened [...]." (Warren et al., 2021, page 1).

According to Butterfly Conservation<fnref n="43" />, 80% of butterfly species have declined in abundance or distribution since the 1970s. In the United States, the situation is even worse than in Europe, where some butterfly species have experienced declines of up to 2% per year in the recent period (Thogmartin et al., 2017; Wepprich et al., 2019). In fact, the decline of wild bees and other pollinators cannot be compensated by an increase in honeybees because they play different roles in crop pollination and do not visit plants in the same way or at the same time (Rader et al., 2016). Therefore, crop yield and quality depend on pollinator biodiversity.

The drivers and risks associated with pollinator decline have been extensively reviewed in the 2016 report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). A summary can be found in Potts et al. (2016). According to IPBES (2016, Chapter 2, pages 30–149), there are five main drivers of change in pollination networks:

1. Land use and its change ("It is well established that habitat loss and degradation [...] affect pollinator diversity, abundance and richness. These changes can negatively affect community stability, pollination networks and the survival and evolutionary potential of pollinator and plant species.")

2. Pesticides, GMOs, veterinary medicines and pollutants ("It is clear that pollinators may be exposed to a wide range of pesticides in both agricultural and urban environments. The risk posed by pesticides is driven by a combination of the toxicity (hazard) and the level of exposure; [...] Insecticides are toxic to insect pollinators and their exposure, and thus the risk posed, is increased if, for example, labels do not provide use information to minimise pollinator exposure or the label is not complied with by the pesticide applicator.")

3. Pollinator diseases and pollinator management ("Bee management is a global and complex driver of pollinator loss. Spreading of diseases by managed honey bees and bumble bees into wild bee species has been shown to present a threat to some wild species and populations.")

4. Invasive alien species ("Invasive predators can directly kill pollinators or disrupt pollinator communities and associated pollination systems, whilst invasive pollinators can outcompete or transmit diseases to native pollinator species or simply be accommodated in the existing pollinator assemblage.")

5. Climate change ("Many plant and pollinator species have moved their ranges, altered their abundance, and shifted their seasonal activities in response to observed climate change over recent decades.")

Using this classification, Dicks et al. (2021) conducted a formal expert elicitation process to assess the regional and global importance of these drivers. Results are presented in Table 14. Globally, land cover and management are the most important drivers of pollinator decline, followed by pesticide

<footnote n="43">⁴³See the latest report *The State of the UK's Butterflies 2022*, available at www.butterfly-conservation.org/state-of-uk-butterflies-2022.</footnote>
<table><caption>Table 14: Assessment of the importance of the top eight drivers of pollinator decline</caption><thead><tr><th>Drivers</th><th>Africa</th><th>Asia Pacific</th><th>Australasia</th><th>Europe</th><th>Latin America</th><th>North America</th><th>Global</th></tr></thead><tbody><tr><td>Land cover</td><td>○</td><td>●</td><td>○</td><td>●</td><td>●</td><td>○</td><td>●</td></tr><tr><td>Land management</td><td>●</td><td>●</td><td>○</td><td>●</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Pesticide use</td><td>○</td><td>●</td><td>○</td><td>○</td><td>●</td><td>○</td><td>○</td></tr><tr><td>Climate change</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td></tr><tr><td>Pests and pathogens</td><td>●</td><td>○</td><td>○</td><td>●</td><td>○</td><td>○</td><td>○</td></tr><tr><td>Pollinator management</td><td>●</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td></tr><tr><td>Invasive alien species</td><td>●</td><td>○</td><td>○</td><td>●</td><td>○</td><td>○</td><td>○</td></tr><tr><td>Genetically modified crops</td><td>●</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td><td>○</td></tr></tbody></table>

The circle size is proportional to the importance score between 1 (not important) and 4 (the most important). The circle color corresponds to the confidence score: ● = well established, ○ = established but incomplete, and ○ = inconclusive.

Source: Dicks et al. (2021, Figure 2, page 1457 & Supplementary Table 2).

use. Climate change, pests and pathogens, pollinator management and invasive alien species are also important, but to a lesser extent, and contribute equally. GMOs are the least important driver. However, there are some strong differences between regions. Pesticide use is very important in Asia Pacific and Latin America. In Europe and North America, land management is the most important issue. The impact of these changes can be divided into two main categories:

* Impact on food production (pollination deficits, yield instability, honey production, food security, wild fruit availability, managed pollinators)

* Impact on biocultural diversity (wild pollinator and plant diversity, aesthetic and cultural values)

Although we have some estimates of these risks, it is currently difficult to predict the future trajectory of pollination ecosystem services and the consequences for human quality of life. The conclusion of Dicks et al. (2021) summarized perfectly what science can say about this issue: “Despite extensive research on pollinator decline, our analysis reveals considerable scientific uncertainty about what this means for human society.” Regarding the impact on food production, the future is not entirely bleak, especially with the potential for hand pollination and advancements in robotic pollination. The impact on biocultural diversity is more complex and harder to address.
## 2.4 Food and feed service

There are several ways to look at food and feed in the context of biodiversity. Food biodiversity refers to the diversity of plants, animals and other organisms used for human consumption. It can be analyzed from two main perspectives. From a production perspective, food biodiversity describes the supply of food in terms of volume (e.g., tonnes produced). From a consumption perspective, it describes the demand for food in terms of nutrient intake, such as calories, proteins, vitamins and minerals. Additional approaches can be explored, such as comparing farmed foods to wild foods, examining the diversity of local versus global food systems, or exploring sustainable versus conventional agricultural practices.

The main source of food is agriculture, which involves food production managed by humans. Historically, wild foods were the sole component of human diets. Today, the proportion of food production attributed to wild foods is relatively small compared to agricultural sources, although it continues to play an important role in certain communities, particularly for indigenous peoples, in certain regions, and in some rural areas<fnref n="44" />. Therefore, we will only consider non-wild foods for which data have been collected by the FAO since 1961 and are freely available for more than 245 countries.

### 2.4.1 Food production

World production of primary crops reached 9.61 billion tonnes in 2022 (Table 15). Since 1961, this figure has been multiplied by a factor of 3.78, representing an annual growth rate of 2.2% over the past sixty years. Cereals and sugar crops account for 31.8% and 22.7% of global production, respectively, while fruits, roots and tubers, and vegetables each contribute approximately 10%. In Table 15 we have also reported the top 20 crops by production. We see that sugar cane has the largest share, accounting for 20% of global primary crop production. In second place is maize with 12.11%. This is followed by wheat (8.41%), rice (8.08%), and oil palm (4.42%). The top five crops account for more than 50% of total production, the top 10 for about 70%, and the top 20 for more than 80%. This indicates a high concentration of production in a small number of crops. In Figure 15, we present the Lorenz curve for the 162 crops in the FAO database. The graph confirms the previous findings and highlights the high concentration, as 10% of the crops account for 80% of the total production volume. Moreover, this lack of diversity is the same in 2022 as it was in 1961, but this does not mean that the structure of crop production has not changed. In fact, we observe that the market shares are very different between 1961 and 2022. For example, potatoes represented 10.7% of total production in 1961, but only 3.9% today. The shares of corn, oil palm fruits, soybeans, onions, cucumbers, yams, and rapeseed have increased significantly, while the shares of sugar beets, barley, and sweet potatoes have experienced notable declines. Figure 16 illustrates the evolution of harvested area over the past sixty years. Between 1961 and 2022, cropland expanded by 51.6%, though this growth was uneven. The period before 2000 saw an annual growth rate of 0.5%, while after 2000, this rate accelerated to 1% per year. As a result, the overall 278% increase in crop production during this period was largely due to productivity gains and shifts in production structure. In Table 15, we report crop yield, which is defined as the ratio between production (expressed in tonnes) and harvested area (expressed in hectares). Yield has increased for all crops, on average by a factor of 2.49. We notice that fruits have a better yield than staples. All these factors explain the dynamics of world crop production.

<footnote n="44">⁴⁴In the early 1990s, it was estimated to be less than 10% worldwide. However, reliable data are lacking. In the European Union, according to Schulp et al. (2014), the amount of wild foods collected is very small compared to total food, and the economic and nutritional value of wild foods is a few thousandths of the total consumption. However, wild foods provide an important cultural ecosystem service, as a wide variety of game (38 species), mushrooms (27 species), and vascular plants (81 species) are collected and consumed by more than 100 million EU citizens.</footnote>
<table><caption>Table 15: World production of primary crops</caption><thead><tr><th rowspan="2">Crop</th><th colspan="4">Production (in billion tonnes)</th><th colspan="2">1961 breakdown</th><th colspan="2">2022 breakdown</th><th colspan="2">Yield (in t/ha)</th></tr><tr><th>1961</th><th>1980</th><th>2000</th><th>2020</th><th>2022</th><th>(in %)</th><th>(% cum.)</th><th>(in %)</th><th>(% cum.)</th><th>1961</th><th>2022</th></tr></thead><tbody><tr><td>Primary crops</td><td>2.54</td><td>4.02</td><td>6.14</td><td>9.38</td><td>9.61</td><td>100.00</td><td>100.00</td><td>100.00</td><td>100.00</td><td>2.61</td><td>6.49</td></tr><tr><td>Cereals</td><td>0.88</td><td>1.55</td><td>2.06</td><td>3.00</td><td>3.06</td><td>34.58</td><td>31.84</td><td>31.84</td><td>31.84</td><td>1.35</td><td>4.18</td></tr><tr><td>Fruit</td><td>0.22</td><td>0.40</td><td>0.68</td><td>1.07</td><td>1.10</td><td>8.87</td><td>11.44</td><td>11.44</td><td>11.44</td><td>7.62</td><td>14.09</td></tr><tr><td>Oil crops</td><td>0.07</td><td>0.15</td><td>0.32</td><td>0.66</td><td>0.68</td><td>2.90</td><td>7.06</td><td>7.06</td><td>7.06</td><td>0.33</td><td>1.01</td></tr><tr><td>Pulses, Roots and Tubers</td><td>0.50</td><td>0.56</td><td>0.75</td><td>0.96</td><td>1.00</td><td>19.56</td><td>10.44</td><td>10.44</td><td>10.44</td><td>4.45</td><td>6.02</td></tr><tr><td>Sugar crops</td><td>0.61</td><td>1.00</td><td>1.50</td><td>2.13</td><td>2.18</td><td>24.02</td><td>22.73</td><td>22.73</td><td>22.73</td><td>38.16</td><td>71.61</td></tr><tr><td>Vegetables</td><td>0.20</td><td>0.29</td><td>0.69</td><td>1.15</td><td>1.17</td><td>7.79</td><td>12.21</td><td>12.21</td><td>12.21</td><td>9.34</td><td>20.13</td></tr><tr><td>Other</td><td>0.06</td><td>0.06</td><td>0.15</td><td>0.41</td><td>0.41</td><td>2.28</td><td>4.29</td><td>4.29</td><td>4.29</td><td></td><td></td></tr><tr><td>Sugar cane</td><td>0.45</td><td>0.73</td><td>1.25</td><td>1.88</td><td>1.92</td><td>17.66</td><td>17.66</td><td>20.00</td><td>20.00</td><td>50.27</td><td>73.67</td></tr><tr><td>Maize (corn)</td><td>0.21</td><td>0.40</td><td>0.59</td><td>1.16</td><td>1.16</td><td>8.09</td><td>25.75</td><td>12.11</td><td>32.11</td><td>1.94</td><td>5.72</td></tr><tr><td>Wheat</td><td>0.22</td><td>0.44</td><td>0.59</td><td>0.76</td><td>0.81</td><td>8.77</td><td>34.52</td><td>8.41</td><td>40.52</td><td>1.09</td><td>3.69</td></tr><tr><td>Rice</td><td>0.22</td><td>0.40</td><td>0.60</td><td>0.77</td><td>0.78</td><td>8.50</td><td>43.02</td><td>8.08</td><td>48.60</td><td>1.87</td><td>4.70</td></tr><tr><td>Oil palm fruit</td><td>0.01</td><td>0.03</td><td>0.12</td><td>0.42</td><td>0.42</td><td>0.54</td><td>43.56</td><td>4.42</td><td>53.02</td><td>3.77</td><td>14.15</td></tr><tr><td>Potatoes</td><td>0.27</td><td>0.24</td><td>0.32</td><td>0.37</td><td>0.37</td><td>10.67</td><td>54.23</td><td>3.90</td><td>56.92</td><td>12.22</td><td>21.07</td></tr><tr><td>Soya beans</td><td>0.03</td><td>0.08</td><td>0.16</td><td>0.36</td><td>0.35</td><td>1.06</td><td>55.29</td><td>3.63</td><td>60.55</td><td>1.13</td><td>2.61</td></tr><tr><td>Cassava, fresh</td><td>0.07</td><td>0.12</td><td>0.18</td><td>0.31</td><td>0.33</td><td>2.81</td><td>58.10</td><td>3.44</td><td>63.99</td><td>7.40</td><td>10.31</td></tr><tr><td>Other vegetables, fresh n.e.c.</td><td>0.06</td><td>0.09</td><td>0.21</td><td>0.29</td><td>0.30</td><td>2.46</td><td>60.55</td><td>3.10</td><td>67.09</td><td>8.42</td><td>14.53</td></tr><tr><td>Sugar beet</td><td>0.16</td><td>0.27</td><td>0.25</td><td>0.25</td><td>0.26</td><td>6.33</td><td>66.88</td><td>2.72</td><td>69.81</td><td>23.17</td><td>60.77</td></tr><tr><td>Tomatoes</td><td>0.03</td><td>0.05</td><td>0.11</td><td>0.19</td><td>0.19</td><td>1.09</td><td>67.97</td><td>1.94</td><td>71.74</td><td>16.43</td><td>37.84</td></tr><tr><td>Barley</td><td>0.07</td><td>0.16</td><td>0.13</td><td>0.16</td><td>0.15</td><td>2.86</td><td>70.83</td><td>1.61</td><td>73.36</td><td>1.33</td><td>3.29</td></tr><tr><td>Bananas</td><td>0.02</td><td>0.04</td><td>0.07</td><td>0.13</td><td>0.14</td><td>0.88</td><td>71.71</td><td>1.41</td><td>74.76</td><td>10.65</td><td>22.75</td></tr><tr><td>Onions and shallots</td><td>0.01</td><td>0.02</td><td>0.05</td><td>0.11</td><td>0.11</td><td>0.55</td><td>72.26</td><td>1.15</td><td>75.91</td><td>11.68</td><td>18.54</td></tr><tr><td>Watermelons</td><td>0.02</td><td>0.03</td><td>0.08</td><td>0.10</td><td>0.10</td><td>0.70</td><td>72.96</td><td>1.04</td><td>76.95</td><td>9.13</td><td>34.27</td></tr><tr><td>Apples</td><td>0.02</td><td>0.03</td><td>0.06</td><td>0.09</td><td>0.10</td><td>0.67</td><td>73.64</td><td>1.00</td><td>77.95</td><td>9.91</td><td>19.86</td></tr><tr><td>Cucumbers and gherkins</td><td>0.01</td><td>0.01</td><td>0.04</td><td>0.09</td><td>0.09</td><td>0.38</td><td>74.01</td><td>0.99</td><td>78.94</td><td>9.43</td><td>43.56</td></tr><tr><td>Yams</td><td>0.01</td><td>0.01</td><td>0.04</td><td>0.08</td><td>0.09</td><td>0.33</td><td>74.34</td><td>0.92</td><td>79.85</td><td>7.23</td><td>8.49</td></tr><tr><td>Rape or colza seed</td><td>0.00</td><td>0.01</td><td>0.04</td><td>0.07</td><td>0.09</td><td>0.14</td><td>74.48</td><td>0.91</td><td>80.76</td><td>0.57</td><td>2.18</td></tr><tr><td>Sweet potatoes</td><td>0.10</td><td>0.14</td><td>0.14</td><td>0.09</td><td>0.09</td><td>3.87</td><td>78.36</td><td>0.90</td><td>81.66</td><td>7.35</td><td>11.92</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.
<figure><img src="image_44.png" /><figcaption>Figure 15: Lorenz curve of world crop production</figcaption></figure>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.

<figure><img src="image_45.png" /><figcaption>Figure 16: Harvested area for crop production</figcaption></figure>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.
We now look at livestock production (Table 16). Like crops, livestock has experienced remarkable growth: +1456% for poultry meat, +517% for eggs, +395% for pork meat, etc. However, the magnitude of the production volume is not the same. In fact, we get a total of less than 1.4 billion tonnes, smaller compared to the 9.6 billion tonnes of crop production.

<table><caption>Table 16: World production of primary livestock (in million tonnes)</caption><thead><tr><th>Livestock</th><th>1961</th><th>1970</th><th>1980</th><th>1990</th><th>2000</th><th>2010</th><th>2020</th><th>2021</th><th>2022</th><th>Growth</th></tr></thead><tbody><tr><td>Eggs</td><td>15</td><td>20</td><td>27</td><td>37</td><td>55</td><td>69</td><td>93</td><td>93</td><td>93</td><td>517%</td></tr><tr><td>Milk</td><td>344</td><td>392</td><td>466</td><td>542</td><td>579</td><td>725</td><td>921</td><td>941</td><td>930</td><td>170%</td></tr><tr><td>Meat</td><td>71</td><td>101</td><td>137</td><td>180</td><td>232</td><td>294</td><td>339</td><td>355</td><td>361</td><td>405%</td></tr><tr><td>Beef & Buffalo</td><td>29</td><td>40</td><td>47</td><td>55</td><td>58</td><td>67</td><td>74</td><td>75</td><td>76</td><td>165%</td></tr><tr><td>Pork</td><td>25</td><td>36</td><td>53</td><td>70</td><td>89</td><td>108</td><td>108</td><td>121</td><td>123</td><td>395%</td></tr><tr><td>Poultry</td><td>9</td><td>15</td><td>26</td><td>41</td><td>69</td><td>99</td><td>135</td><td>136</td><td>139</td><td>1456%</td></tr><tr><td>Sheep & Goat</td><td>6</td><td>7</td><td>7</td><td>10</td><td>11</td><td>14</td><td>16</td><td>16</td><td>17</td><td>176%</td></tr><tr><td>Other</td><td>3</td><td>3</td><td>4</td><td>4</td><td>4</td><td>6</td><td>6</td><td>6</td><td>6</td><td>106%</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.

The remarkable growth in primary crops and livestock can be attributed to three key factors: expansion of cultivated area (although we have seen that only one-third of this growth is due to this factor), the adoption of intensive agricultural practices, and the increased use of inputs such as fertilizers and pesticides. Fertilizer use has increased sixfold in the last sixty years, while pesticide use has doubled between 1990 and 2022 (Table 17).

<table><caption>Table 17: Agricultural use of inputs (fertilizers and pesticides)</caption><thead><tr><th rowspan="2">Input</th><th colspan="5">Agricultural use (in million tonnes)</th><th colspan="5">Use par area of cropland (in kg/ha)</th></tr><tr><th>1961</th><th>1980</th><th>2000</th><th>2020</th><th>2022</th><th>1961</th><th>1980</th><th>2000</th><th>2020</th><th>2022</th></tr></thead><tbody><tr><td>Fertilizer</td><td>31.0</td><td>116.6</td><td>135.2</td><td>201.7</td><td>185.4</td><td>20.8</td><td>76.8</td><td>85.9</td><td>123.5</td><td>113.1</td></tr><tr><td>Nitrogen</td><td>11.5</td><td>60.6</td><td>81.0</td><td>114.7</td><td>108.1</td><td>7.6</td><td>39.6</td><td>51.3</td><td>69.6</td><td>65.4</td></tr><tr><td>Phosphate</td><td>10.9</td><td>31.8</td><td>32.5</td><td>47.8</td><td>41.9</td><td>7.5</td><td>21.4</td><td>21.0</td><td>29.8</td><td>26.0</td></tr><tr><td>Potash</td><td>8.6</td><td>24.2</td><td>21.7</td><td>39.3</td><td>35.5</td><td>5.7</td><td>15.8</td><td>13.7</td><td>24.1</td><td>21.7</td></tr><tr><td>Pesticide</td><td></td><td></td><td>2.2</td><td>3.4</td><td>3.7</td><td></td><td></td><td>1.5</td><td>2.2</td><td>2.4</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/RFN, www.fao.org/faostat/en/#data/RP & Author's calculations.

**Remark 5** The figures presented in this paragraph can be analyzed at the country or regional level. In this case, we observe large differences between regions of the world, for example between the Americas and Africa, or between developed and developing countries (FAO, 2023b).

## 2.4.2 Food consumption

Table 18 shows the food supply<fnref n="45" /> per capital and per day for the different regions of the world. In general, food supply is assessed along three primary dimensions: energy intake, protein intake, and fat intake. In 2022, the global average daily per capita intake was 2985 kilocalories of energy<fnref n="46" />, 92 grams of protein, and 87 grams of fat. Over the past sixty years, these figures have increased by 36%, 51%, and 81%, respectively. However, these averages mask significant differences between regions. For example, fat intake is currently only 41 g/capita/day in Middle Africa, while it reaches 177 g/capita/day in North America. These differences are even more pronounced when we look

<footnote n="45">⁴⁵Food supply measures the amount available for consumption at the end of the supply chain and does not include consumption waste.</footnote>

<footnote n="46">⁴⁶In the context of nutrition, 1 Calorie (with a capital C) is used as a shorthand for 1 kilocalorie (kcal).</footnote>
<table><caption>Table 18: Food supply per capital per day (energy, protein & fat)</caption><thead><tr><th rowspan="2">Region</th><th colspan="3">Energy<br>(in Cal/capita/day)</th><th colspan="3">Protein<br>(in g/capita/day)</th><th colspan="3">Fat<br>(in g/capita/day)</th></tr><tr><th>1961</th><th>1990</th><th>2022</th><th>1961</th><th>1990</th><th>2022</th><th>1961</th><th>1990</th><th>2022</th></tr></thead><tbody><tr><td>Africa</td><td>1993</td><td>2291</td><td>2567</td><td>53</td><td>59</td><td>66</td><td>40</td><td>47</td><td>56</td></tr><tr><td>Eastern Africa</td><td>1989</td><td>1925</td><td>2263</td><td>56</td><td>50</td><td>59</td><td>29</td><td>32</td><td>47</td></tr><tr><td>Middle Africa</td><td>2018</td><td>1847</td><td>2312</td><td>49</td><td>45</td><td>46</td><td>36</td><td>44</td><td>41</td></tr><tr><td>Northern Africa</td><td>1920</td><td>2851</td><td>3142</td><td>53</td><td>78</td><td>91</td><td>38</td><td>60</td><td>74</td></tr><tr><td>Southern Africa</td><td>2603</td><td>2755</td><td>2713</td><td>70</td><td>73</td><td>79</td><td>58</td><td>64</td><td>91</td></tr><tr><td>Western Africa</td><td>1909</td><td>2199</td><td>2644</td><td>46</td><td>52</td><td>65</td><td>46</td><td>49</td><td>57</td></tr><tr><td>Americas</td><td>2559</td><td>2953</td><td>3392</td><td>77</td><td>82</td><td>104</td><td>78</td><td>97</td><td>135</td></tr><tr><td>Northern America</td><td>2873</td><td>3447</td><td>3881</td><td>95</td><td>107</td><td>122</td><td>110</td><td>138</td><td>177</td></tr><tr><td>Central America</td><td>2180</td><td>2796</td><td>3173</td><td>59</td><td>73</td><td>94</td><td>48</td><td>69</td><td>101</td></tr><tr><td>Caribbean</td><td>1992</td><td>2390</td><td>2828</td><td>47</td><td>57</td><td>75</td><td>42</td><td>65</td><td>78</td></tr><tr><td>South America</td><td>2329</td><td>2599</td><td>3111</td><td>63</td><td>65</td><td>95</td><td>49</td><td>73</td><td>118</td></tr><tr><td>Asia</td><td>1805</td><td>2414</td><td>2944</td><td>47</td><td>61</td><td>93</td><td>25</td><td>49</td><td>78</td></tr><tr><td>Central Asia</td><td></td><td></td><td>3169</td><td></td><td></td><td>103</td><td></td><td></td><td>104</td></tr><tr><td>Eastern Asia</td><td>1594</td><td>2564</td><td>3361</td><td>44</td><td>69</td><td>124</td><td>18</td><td>56</td><td>95</td></tr><tr><td>Southern Asia</td><td>2014</td><td>2242</td><td>2584</td><td>52</td><td>54</td><td>72</td><td>30</td><td>40</td><td>62</td></tr><tr><td>South-eastern Asia</td><td>1836</td><td>2178</td><td>2880</td><td>40</td><td>48</td><td>80</td><td>27</td><td>41</td><td>69</td></tr><tr><td>Western Asia</td><td>2501</td><td>3273</td><td>3128</td><td>76</td><td>93</td><td>93</td><td>57</td><td>84</td><td>101</td></tr><tr><td>Europe</td><td>3041</td><td>3367</td><td>3471</td><td>90</td><td>104</td><td>112</td><td>89</td><td>125</td><td>140</td></tr><tr><td>Eastern Europe</td><td>3100</td><td>3360</td><td>3375</td><td>95</td><td>105</td><td>109</td><td>73</td><td>108</td><td>121</td></tr><tr><td>Northern Europe</td><td>3176</td><td>3214</td><td>3402</td><td>91</td><td>96</td><td>113</td><td>131</td><td>134</td><td>141</td></tr><tr><td>Southern Europe</td><td>2838</td><td>3469</td><td>3519</td><td>82</td><td>107</td><td>116</td><td>72</td><td>136</td><td>149</td></tr><tr><td>Western Europe</td><td>3016</td><td>3374</td><td>3615</td><td>89</td><td>103</td><td>113</td><td>113</td><td>149</td><td>162</td></tr><tr><td>Oceania</td><td>3021</td><td>3139</td><td>3101</td><td>100</td><td>105</td><td>101</td><td>108</td><td>126</td><td>128</td></tr><tr><td>Australasia</td><td>3060</td><td>3188</td><td>3417</td><td>103</td><td>109</td><td>115</td><td>111</td><td>129</td><td>152</td></tr><tr><td>Melanesia</td><td>2534</td><td>2547</td><td>2314</td><td>54</td><td>65</td><td>66</td><td>60</td><td>86</td><td>66</td></tr><tr><td>Micronesia</td><td>2424</td><td>2622</td><td>2937</td><td>51</td><td>64</td><td>86</td><td>116</td><td>94</td><td>126</td></tr><tr><td>Polynesia</td><td>2239</td><td>2683</td><td>2959</td><td>55</td><td>77</td><td>107</td><td>73</td><td>107</td><td>117</td></tr><tr><td>World</td><td>2196</td><td>2621</td><td>2985</td><td>61</td><td>70</td><td>92</td><td>48</td><td>67</td><td>87</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/FBS, www.fao.org/faostat/en/#data/FBSH & Author's calculations.

at countries. Figure 17 shows the dispersion of food supply for the 200 countries included in the FAO database. We can see that the dispersion has not decreased since 1961, in fact it has increased! Countries with the lowest average energy intake include Burundi, Lesotho, Somalia, Haiti, and Madagascar, while those with the highest energy intake are Israel, the United States, Ireland, Belgium, and Turkey. For protein intake, the lowest levels are found in the Democratic Republic of the Congo, Madagascar, Burundi, Somalia, and Mozambique, while Iceland, Israel, Ireland, Mongolia, and Montenegro have the highest. In terms of fat intake, Burundi, DR Congo, Madagascar, Rwanda, and Cambodia rank the lowest, while Belgium, Austria, the United States, Israel, and Germany rank the highest. This reflects economic disparities, but also some of the dietary habits of the countries with the highest levels. The vegetal/animal structure of the human diet also has an impact (Table 19). In fact, protein intake from animal sources has increased over the past sixty years, while the contribution of animal products to fat intake has decreased.
<figure><img src="image_46.png" /><figcaption>Figure 17: Country dispersion of food supply</figcaption></figure>

Source: www.fao.org/faostat/en/#data/FBS, www.fao.org/faostat/en/#data/FBSH & Author's calculations.

<table><caption>Table 19: Split of food supply between vegetal and animal products</caption><thead><tr><th rowspan="2">Food Origin</th><th colspan="3">1961</th><th colspan="3">2022</th></tr><tr><th>Energy</th><th>Protein</th><th>Fat</th><th>Energy</th><th>Protein</th><th>Fat</th></tr></thead><tbody><tr><td>Vegetal</td><td>1 858</td><td>41.80</td><td>22.80</td><td>2 460</td><td>53.45</td><td>51.33</td></tr><tr><td>Animal</td><td>338</td><td>19.66</td><td>24.72</td><td>525</td><td>38.08</td><td>35.98</td></tr><tr><td>Total</td><td>2 196</td><td>61.46</td><td>47.52</td><td>2 945</td><td>91.52</td><td>87.31</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/FBS, www.fao.org/faostat/en/#data/FBSH & Author's calculations.

### 2.4.3 Food security

Biodiversity is closely linked to food security, as it provides the foundation for resilient and sustainable food systems. This interconnectedness has several dimensions. Moreover, the concept of double materiality is highly relevant, as biodiversity impacts food production, while food and agricultural production also has a significant impact on biodiversity. In this context, it is challenging to classify and list all the dimensions. Therefore, we will focus on a few key dimensions that are essential for food security. The first dimension is the genetic diversity of crops and livestock. Below is an excerpt from the press release of the FAO 2019 biodiversity assessment publication (FAO, 2019):

> "Less biodiversity means that plants and animals are more vulnerable to pests and diseases. Compounded by our reliance on fewer and fewer species to feed ourselves, the increasing loss of biodiversity for food and agriculture puts food security and nutrition at risk." (José Graziano da Silva, FAO Director-General, 22 February 2019, Rome).
Many crop species are no longer cultivated because production is concentrated on the most profitable crops. Over time, this has led to an industrial selection of species, resulting in the homogenization and globalization of the human diet. In this context, we are more vulnerable when a species faces problems such as disease. Here are some examples:

* Irish potato famine (1845–1852)

The main cause was the infection of potato crops by the potato blight (caused by the fungus-like microorganism *Phytophthora infestans*). This blight led to one million deaths and caused the mass emigration of another million people. The severity of the disease was largely due to Ireland's dependence on a single crop, the potato.

* Coffee leaf rust outbreak in Sri Lanka (1860–1890)

Coffee leaf rust (CLR) is a disease of the coffee plant caused by the fungus *Hemileia vastatrix*. In the 1860s, coffee production was an important resource for Sri Lanka, but the outbreak of coffee leaf rust destroyed the coffee industry in the region and led to a shift to tea cultivation.

* Panama disease in bananas (1950s)

Panama disease, caused by the fungus *Fusarium oxysporum*, infects banana plants and nearly eradicated the Gros Michel variety in the 1950s. This led to its replacement with the Cavendish variety, which now faces a similar threat from a new strain of the disease.

* Southern corn leaf blight in the United States (1970)

Southern corn leaf blight is a disease of corn caused by the plant pathogen *Bipolaris maydis* (Race O, Race C, and Race T). The 1970 epidemic in the USA was triggered by the widespread use of Texas male sterile cytoplasm corn, which made 90% of hybrid crops susceptible to the newly emerged Race T pathogen. This outbreak, which began in the southern U.S. and spread rapidly in the north, destroyed approximately 15% of corn production.

* Wheat stem rust Ug99 in Africa (1998–present)

Ug99 is a strain of wheat stem rust caused by the fungus *Puccinia graminis*. It was first identified in 1998 and has spread to several countries in Africa and the Middle East. It poses a significant threat to global wheat production due to the high susceptibility of many wheat varieties.

* Citrus greening disease in Florida (2005–present)

Citrus greening disease, caused by *Liberibacter bacteria*, affects citrus plants and exists in three forms: a heat-tolerant Asian type and heat-sensitive African and American types. First identified in 1929 and reported in southern China in 1943, the disease has severely impacted citrus production in the United States, particularly in Florida, where orange production has declined by more than 50% since 2005.

These diseases highlight the risks of focusing on one or a few crop species. In fact, reliance on a limited number of crop species increases the vulnerability of agriculture to disease. When a single pathogen targets a widely grown crop, such as Panama disease in bananas or Southern corn leaf blight in maize, the impact can be catastrophic, causing widespread losses. Biodiversity is then essential for building resilience to future outbreaks. Coffee is a typical example. According to Davis et al. (2019), coffee production is concentrated in a small number of coffee species. In particular, Arabica (*Coffea arabica*) and Robusta (*Coffea canephora*) account for 60% and 40% of traded coffee, respectively, leaving little room for other species. Arabica coffee has been cultivated for at least several hundred years, which is not the case with Robusta, which was first cultivated in the mid-1800s. Robusta coffee went from being a minor African crop to a major global commodity in only
about 150 years, and Davis et al. (2019) concluded that “*Robusta coffee* provides a good example of *how a (relatively) newly discovered wild species has transformed a globally important crop.*” One of the main reasons for its success is its resistance to coffee leaf rust. Of the 124 known coffee species worldwide, their conservation status according to the IUCN extinction risk classification is as follows: 13 are Critically Endangered (CR); 40 are Endangered (EN); 22 are Vulnerable (VU); 9 are Near Threatened (NT); 26 are Least Concern (LC); 14 are Not Evaluated (NE) or Data Deficient (DD). This means that 75% of coffee species are threatened with extinction (Davis et al., 2019, Figure 1, page 2). Therefore, coffee production is at significant risk if existing diseases<fnref n="47" /> become more severe or if new diseases emerge, as the number of alternative species that could potentially replace today’s Arabica or Robusta varieties has declined over the past century.

The previous example deals with intraspecific diversity (for example, the different types of coffee in the genus *Coffea*), but biodiversity loss is also related to interspecific diversity (for example, the different crops in the clade *Mesangiospermae*). While intraspecific diversity of the food supply has declined in recent times, interspecific diversity has increased with the diversification of diets and trade in commodities, especially in developed countries. Many people now eat exotic fruits, fish and vegetables that would not have been available less than a century ago. Agricultural specialization and the diversity of human diets explain the growth of agricultural trade. Table 20 shows that the export share of most crops and commodities has increased. For example, avocado exports represented less than 1% of production in 1961, compared to more than 35% of production in 2021. FAO statistics show that the largest increases (more than 30% between 1961 and 2021) are for cherries, coconut oil, cranberries, kiwi, lentils, mustard seeds, natural honey, olive oil, peas, quinoa, and soybeans. Looking at OECD statistics, the largest increases (+20% between 1990 and 2023) are for edible fish meals, skim milk powder, soybeans, and sugar. Agricultural trade is a resilient factor in food security, but it also reveals the vulnerability of some countries that have specialized in the most profitable crops.

Box 8: Founder crops

The concept of “founder crops” was introduced by Zohary and Hopf (1988). The authors proposed that eight plant species were first domesticated by early farming communities, laying the foundation of early Neolithic agriculture in Southwest Asia (the Fertile Crescent region of the Near East) around 10 500 years BP. These crops are thought to form the basis of modern agriculture in Europe, Southwest Asia, South Asia, and North Africa. The original founder crops included three cereals (emmer wheat, einkorn wheat, and barley), four pulses (lentil, pea, chickpea, and bitter vetch), and flax.

Subsequent research has suggested that many other species could also be considered as founder crops. This list has been extended for various regions and may include rice and foxtail millet in the Yangtze and Yellow River valleys (about 9 500 years BP), maize, squash, and common bean in southwest Mexico (5 300 years BP), potato, quinoa, and common bean in the Central Andes (5 100 years BP), as well as goosefoot, sunflower, and squash in the Eastern United States (5 100 years BP).

<footnote n="47">⁴⁷There are many coffee diseases that can be classified into four main categories: bacterial diseases, fungal diseases, root diseases, and viral diseases. Here are some examples: anthracnose (*Colletotrichum*), bacterial blight of coffee (*Pseudomonas syringae*), black rot (*Koleroga noxia*), brown eye spot (*Cercospora coffeicola*), cercospora leaf spot (*Cercospora coffeicola*), coffee leaf rust (*Hemileia vastatrix*), coffee berry disease (*Colletotrichum kahawae*), coffee ringspot virus (*Brevipalpus phoenicis*), coffee wilt disease (*Fusarium xylarioides*), root-knot nematode disease (*Meloidogyne*).</footnote>
<table><caption>Table 20: Share of world crop production exported (in %)</caption><thead><tr><th>Crop</th><th>1961</th><th>2021</th><th>Crop</th><th>1961</th><th>2021</th></tr></thead><tbody><tr><td>Apples</td><td>9.4</td><td>8.8</td><td>Olive oil</td><td>14.9</td><td>66.2</td></tr><tr><td>Apricots</td><td>5.0</td><td>8.6</td><td>Onions and shallots</td><td>2.0</td><td>9.1</td></tr><tr><td>Avocados</td><td>0.2</td><td>36.3</td><td>Oranges</td><td>16.3</td><td>10.0</td></tr><tr><td>Bananas</td><td>16.6</td><td>19.3</td><td>Peaches and nectarines</td><td>6.0</td><td>7.0</td></tr><tr><td>Barley</td><td>9.9</td><td>30.0</td><td>Peas</td><td>4.0</td><td>48.7</td></tr><tr><td>Blueberries</td><td>36.9</td><td>39.7</td><td>Persimmons</td><td>0.4</td><td>14.0</td></tr><tr><td>Cauliflowers</td><td>6.4</td><td>6.1</td><td>Pineapples</td><td>2.8</td><td>12.7</td></tr><tr><td>Cherries</td><td>2.9</td><td>35.2</td><td>Pomelos</td><td>10.3</td><td>11.0</td></tr><tr><td>Coconut oil</td><td>21.1</td><td>80.6</td><td>Potatoes</td><td>1.0</td><td>3.8</td></tr><tr><td>Cranberries</td><td>0.0</td><td>50.9</td><td>Quinoa</td><td>0.0</td><td>68.8</td></tr><tr><td>Cucumbers</td><td>1.5</td><td>3.5</td><td>Sesame seeds</td><td>11.0</td><td>32.2</td></tr><tr><td>Dates</td><td>14.0</td><td>19.1</td><td>Soybeans</td><td>15.5</td><td>43.2</td></tr><tr><td>Eggplants</td><td>0.2</td><td>1.1</td><td>Spinach</td><td>0.3</td><td>1.1</td></tr><tr><td>Kiwi fruit</td><td>0.0</td><td>36.4</td><td>Strawberries</td><td>5.4</td><td>11.1</td></tr><tr><td>Lentils</td><td>6.5</td><td>67.5</td><td>Tomatoes</td><td>3.9</td><td>4.4</td></tr><tr><td>Maize</td><td>6.8</td><td>16.2</td><td>Vanilla</td><td>73.8</td><td>91.6</td></tr><tr><td>Mustard seeds</td><td>19.3</td><td>53.8</td><td>Watermelons</td><td>0.9</td><td>4.7</td></tr><tr><td>Natural honey</td><td>11.0</td><td>42.3</td><td>Wheat</td><td>17.8</td><td>25.9</td></tr><tr><td>Commodity</td><td>1990</td><td>2023</td><td>Commodity</td><td>1990</td><td>2023</td></tr><tr><td>Beef meat</td><td>9.2</td><td>18.2</td><td>Pork meat</td><td>1.9</td><td>8.7</td></tr><tr><td>Butter</td><td>10.0</td><td>7.8</td><td>Poultry meat</td><td>8.5</td><td>11.2</td></tr><tr><td>Cheese</td><td>4.0</td><td>13.6</td><td>Pulses</td><td>10.5</td><td>19.8</td></tr><tr><td>Cotton</td><td>24.2</td><td>36.5</td><td>Rice</td><td>3.4</td><td>10.1</td></tr><tr><td>Edible fish meals</td><td>44.7</td><td>67.6</td><td>Roots and tubers</td><td>7.3</td><td>7.8</td></tr><tr><td>Eggs</td><td>2.6</td><td>1.6</td><td>Sheep meat</td><td>12.2</td><td>9.0</td></tr><tr><td>Fish</td><td>15.4</td><td>23.0</td><td>Skim milk powder</td><td>26.4</td><td>57.9</td></tr><tr><td>Fresh dairy products</td><td>0.0</td><td>0.1</td><td>Soybeans</td><td>26.6</td><td>45.1</td></tr><tr><td>Maize</td><td>12.8</td><td>15.3</td><td>Sugar</td><td>9.8</td><td>36.8</td></tr><tr><td>Oilseed meals</td><td>24.2</td><td>24.5</td><td>Vegetable oils</td><td>24.3</td><td>37.2</td></tr><tr><td>Other coarse grains</td><td>7.7</td><td>14.0</td><td>Wheat</td><td>19.4</td><td>24.1</td></tr><tr><td>Other oilseeds</td><td>15.2</td><td>13.6</td><td>Whole milk powder</td><td>45.9</td><td>49.9</td></tr></tbody></table>

Source: www.fao.org/faostat/en/#data/QCL, www.fao.org/faostat/en/#data/TCL, https://data-explorer.oecd.org & Author's calculations.

A typical example of crop expansion is maize (Pollan, 2007; Hartigan, 2017). In 2022, maize (*Zea mays*) was the world's most widely produced grain crop (1.16 billion tonnes, covering the second-largest cultivated area (203.5 million hectares) and achieving the highest grain yield (5.72 tonnes per hectare). Today, maize appears in a wide range of foods, including candy corn, corn dogs, corn flakes, corn soup, cornstarch, corn tortillas, cornbread, polenta, popcorn, tamales, and more. This proliferation is especially noticeable in the Americas. For instance, Maize is the focus of the documentary film *King Corn*, which was released in October 2007. The film explores the trend of increased corn production and its impact on American society. However, maize has not always been the dominant crop that “*has conquered the world.*” Native to Central America, maize was introduced to Europe in the early 16th century following Christopher Columbus's voyages to the Americas. Initially brought to Spain by explorers returning from the New World, maize gradually spread
across southern Europe, the Mediterranean, and eventually to Africa and Asia. Its global spread was largely due to its adaptability to different climates and soil conditions. Figure 18 illustrates the expansion of maize in world agriculture. The first panel shows the area harvested. In 1961, this was 105.6 million hectares — less than the area cultivated for rice (115.4 million hectares) and wheat (204.2 million hectares). By 2022, the area cultivated for maize is nearly equal to that of wheat and surpasses that of rice. Maize production has accelerated since 2000, driven by a significant expansion of harvested area and the introduction of genetically modified (GMO) maize varieties. One of the key issues with maize production is its substitution effect on the supply of other crops. In particular, the primary use of maize is not for direct human consumption but as animal feed. Using FAO statistics, we report below the breakdown of maize use$^{48}$:

<table><thead><tr><th>Year</th><th>Animal feed</th><th>Human food</th><th>Losses</th><th>Seed</th><th>Processing</th><th>Other uses</th></tr></thead><tbody><tr><td>2010</td><td>55.3%</td><td>13.6%</td><td>3.5%</td><td>0.7%</td><td>5.7%</td><td>21.2%</td></tr><tr><td>2022</td><td>60.4%</td><td>11.4%</td><td>5.2%</td><td>0.7%</td><td>5.8%</td><td>16.5%</td></tr></tbody></table>

60% of maize is used as animal feed, mainly for poultry and cattle. Direct human consumption accounts for only 11% of total production, which is less than the *other uses* category. In fact, a significant portion of maize (between 10% and 20%) is processed to produce ethanol, a biofuel used primarily in gasoline blends.

<figure><img src="image_47.png" /><figcaption>Figure 18: Area harvested, production and yield of cereal crops</figcaption></figure>

Source: www.fao.org/faostat/en/#data/QCL & Author's calculations.

The previous issue relates to the Earth's capacity to provide all necessary ecosystem functions without compromising others. Here, the *Do No Significant Harm (DNSH)* concept plays a crucial

<footnote>$^{48}$We first calculate the net supply quantity with the following equations: Supply quantity = Production + Imports - Exports - Stock variation. Then, we use the following decomposition: Supply quantity = Feed + Seed + Losses + Processing + Other uses (non-food) + Tourist consumption + Residuals + Food.</footnote>