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We are facing an unprecedented biodiversity crisis : 25% of known species are threatened and extinction rates are higher than on average in the last 10 million years [1]. Concrete actions are taken around the globe by people, companies and governments. These actions hopefully have a positive impact on biodiversity, hence the importance of reliable metrics to prove it. In this article, you will learn about several biodiversity indicators, going from local to global scale.
A diversity of definitions
Biodiversity encompasses many concepts from the diversity of living organisms, the diversity of species, the diversity of genes within each species, and the organisation and distribution of ecosystems [2]. Here we will address biodiversity measurements relative to the diversity of species, although metrics for other components of biodiversity (genes, interactions, traits) are equally important to measure.
Intuitively, diversity is defined by richness and evenness: a community made up of 6 species is more diverse than a community of 2 species (richness), and a community of evenly distributed individuals from 3 species is more diverse than another one made up of a dominant species and two rare species (evenness) (Fig. 2).
Local biodiversity indicators
Commonly used metrics include species occurrence, richness, and abundance. Occurrence data reveal which species are present at a given place and time (Fig. 3).
Species richness is the number of species in a site. Abundance refers to the number of individuals of each species. Weighted indices combining both richness and evenness (using abundance data) include Simpson and Shannon indices which are often used in scientific papers on biodiversity.
Local biodiversity metrics are usually computed for each taxa separately because data are collected by group (for instance: woody vegetation, invertebrates, birds, bats), trends can vary between groups, and the consequences of change are not similar in all groups (groups are not interchangeable: the impact of the loss of two plant species is different from the impact of the loss of two bird species) [3].
From local to regional metrics
The scale is as critical as the object of measurement in ecological studies. Frequently accepted scales are local (alpha-diversity: species richness in one site) and regional (gamma-diversity: species richness in the landscape). It is also interesting to quantify the differences between sites within a region, this is beta-diversity [4] (Fig. 4). Conservation strategies need to target the maximisation of either alpha, beta or gamma diversity because changes occurring at one scale can be countered at another scale. Beta diversity is essential to adequately upscale local data to regional or global scale [4].
Global biodiversity indicators
Comparing biodiversity levels between different ecological regions to yield a global indicator can be tricky. One solution is to harmonize measurements collected in different regions with community-based weights: biodiversity metrics are normalized by the mean value of each metric in a region or by a baseline value. Global biodiversity indicators have to be quantitative, consensual, consistent through different scenarios of change, conceptually simple, and sensitive to early biodiversity changes in ordinary, keystone, and rare species. Some indicators in use are PLS (potential loss of species within one year based on land use, species mean abundance, and species vulnerability), MSA (mean species abundance compared to reference values in a similar pristine ecosystem), BII (biodiversity intactness index: mean abundance for a group of species in a given area compared to a reference population), LPI (living planet index, a monitoring of populational changes in global vertebrate biodiversity based on aggregated time-series, see Fig. 5).
Another interesting approach uses indirect metrics to assess biodiversity. GEO BON developed a set of essential biodiversity variables (EBVs) which capture biodiversity change in in situ and remote sensing data [5]. Remote sensed data include ecosystem disturbance (characterization of fire or flood disturbance, ecosystem fragmentation), habitat structure (leaf area index, land cover, above-ground biomass), plant community composition, and plant species physiology (foliar N/P/K content, net primary productivity). UNEP-WCMC also produced a list of potential indirect indicators to assess biodiversity, such as protected area coverage, red list index related to pollution, agricultural practices, and number of alien species.
Limitations
This approach assumes that relationships between external variables and biodiversity are well understood anywhere in the world, which is currently not the case. This leads to limited efficiency in conservation strategies based on indirect measurements. For instance, assessment of biodiversity offsets mostly rely on habitat attributes (vegetation cover, land use) and area measurements, whereas conservation strategies focus on direct measurement of biodiversity and connectivity [6]. On the positive side, indirect metrics shed light on causes of biodiversity change in the world, without being limited to illustrations of population trends.
Although global biodiversity indicators are attractive communication tools for policy-makers and companies, these indicators rely heavily on modelling and can lead to misinterpretation due to hidden impacts on different taxa and/or at different scales. A combination of local and global indices might be the best available option - for now - to correctly assess biodiversity and the efficiency of conservation strategies.
References
1 : S. Díaz, J. Settele, E. S. Brondízio, H. T. Ngo, M. Guèze, J. Agard, A. Arneth, P. Balvanera, K. A. Brauman, S. H. M. Butchart, K. M. A. Chan, L. A. Garibaldi, K. Ichii, J. Liu, S. M. Subramanian, G. F. Midgley, P. Miloslavich, Z. Molnár, D. Obura, A. Pfaff, S. Polasky, A. Purvis, J. Razzaque, B. Reyers, R. Roy Chowdhury, Y. J. Shin, I. J. Visseren-Hamakers, K. J. Willis, and C. N. Zayas (eds.). IPBES: Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. 2019. IPBES secretariat, Bonn, Germany. 56 pages. https://doi.org/10.5281/zenodo.3553579
2 : https://www.insee.fr/en/metadonnees/definition/c1264
3 : Yoccoz NG, Ellingsen KE, Tveraa T. Biodiversity may wax or wane depending on metrics or taxa. Proc Natl Acad Sci. 2018;115(8):1681-1683. doi:10.1073/pnas.1722626115
4 : Socolar JB, Gilroy JJ, Kunin WE, Edwards DP. How Should Beta-Diversity Inform Biodiversity Conservation? Trends Ecol Evol. 2016;31(1):67-80. doi:10.1016/j.tree.2015.11.005
5 : Skidmore AK, Coops NC, Neinavaz E, et al. Priority list of biodiversity metrics to observe from space. Nat Ecol Evol. 2021;5(7):896-906. doi:10.1038/s41559-021-01451-x
6 : Marshall E, Wintle BA, Southwell D, Kujala H. What are we measuring? A review of metrics used to describe biodiversity in offsets exchanges. Biol Conserv. 2020;241:108250. doi:10.1016/j.biocon.2019.108250