What is a unit of nature? Measurement challenges in the emerging biodiversity credit market

Abstract

Bending the curve of biodiversity loss requires the business and financial sectors to disclose and reduce their biodiversity impacts and help fund nature recovery. This has sparked interest in developing generalizable, standardized measurements of biodiversity-essentially a 'unit of nature'. We examine how such units are defined in the rapidly growing voluntary biodiversity credits market and present a framework exploring how biodiversity is quantified, how delivery of positive outcomes is detected and attributed to the investment and how the number of credits issued is adjusted to account for uncertainties. We demonstrate that there are deep uncertainties throughout the process and question if the benefits of biodiversity credits, and other efforts to abstract nature to a single unit, outweigh the harms. Credits can only be positive for biodiversity if they are used with unprecedentedly strict regulation that ensures businesses mostly avoid negative impacts and if they are purchased to quantify positive contributions rather than as direct offsets. While there may be a role for markets in attracting conservation funding, they will only ever be part of the solution, especially for the many aspects of nature that cannot be reduced to a unit.

Keywords: additionality; contribution; credits; fungible; leakage; quantify.

Figure 1.

(a) The stages biodiversity credit methodologies go through to create a unit of nature that can be traded to generate revenue for conservation. Numbers in stage 2 ('quantifying’) are normalized measures of each metric. (b) The key question being answered at each stage, and a worked example for a hypothetical credit (note bold, coloured text could be replaced by another decision, see figures 2–5 and electronic supplementary material, tables S1–S5 for full details). (c) Key challenges associated with each stage.

Figure 2.

Decisions taken within the ‘framing’ stage (see figure 1). ‘Any ecosystem’ restoration credit (example 1) and a tropical forest conservation credit (example 2). Bold, coloured text in column 2 shows what decision has been taken by the example credit; this text could be replaced by other decisions depending on answers to the questions shown in column 3 (see electronic supplementary material, table S2 for more details).

Figure 3.

Decisions taken within the ‘quantifying’ stage (see figure 1). ‘Any ecosystem’ restoration credit quantified by a basket of metrics (example 1) and a tropical forest conservation credit quantified via a binary condition (example 2). Bold, coloured text in column 2 shows what decision has been taken by the example credit; this text could be replaced by other decisions depending on answers to the questions shown in column 3 (see electronic supplementary material, table S3 for more details).

Figure 4.

Decisions taken within the ‘detecting’ stage (see figure 1). ‘Any ecosystem’ credit, quantified continuously (example 1) and a tropical forest conservation credit quantified via a binary condition (example 2). Example 1 has been expanded into 1a (restoration) and 1b (conservation), to demonstrate how conservation and restoration are often detected when the ecosystem is quantified continuously. Bold, coloured text in column 2 shows what decision has been taken by the example credit; this text could be replaced by other decisions depending on answers to the questions shown in column 3 (see electronic supplementary material, table S4 for more details).

Figure 5.

Decisions taken within the ‘adjusting’ stage (see figure 1). Showing just one example because adjusting decisions are agnostic to credit type. Bold, coloured text in column 2 shows what decision has been taken by the example credit, this text could be replaced by other decisions depending on answers to the questions shown in column 3 (see electronic supplementary material, table S5 for more details).