Terrascape Protocol for Nature Credits

Methodology to quantify Nature Credits

One Nature Credit represents a 1% increase in the Ecosystem Integrity Index (EII) per hectare within the defined landscape.

Ecosystem Integrity Index (EII) = Arithmetic average (Human Modification Index, Terrascape Biodiversity Intactness Index, Net Primary Productivity Ratio )

The three primary attributes of ecosystem integrity are its structure, composition, and function. The three variables in the equation above – Human Modification Index, Terrascape Biodiversity Intactness Index, and Net Primary Productivity Ratio – are the indicators of these three attributes.

The first attribute of ecosystem integrity is the ecosystem structure. To measure structure, a Human Modification Index (HMI) layer is constructed using the techniques outlined in Kennedy et al. (2019). This involves incorporating various pressure layers such as human settlement (population density and built-up areas), agriculture (cropland and livestock), transportation (major roads, minor roads, two tracks, and railroads), mining, energy production (oil wells and wind turbines), and electrical infrastructure (powerlines and nighttime lights). The identical pressure intensities detailed in Kennedy et al. (2019) are applied. Subsequently, the human modification layer undergoes inversion to convert it into an equivalent of the habitat quality and extent layer described in Beyer et al. (2019). Lastly, their methodology is employed to introduce landscape pressure and fragmentation influences, resulting in the ultimate structure layer. These procedures involve the use of a moving window that compares the quality of a grid cell with that of neighbouring cells, defined as cells within a 27 km distance. All spatial processing was conducted in Google Earth Engine with a resolution of 30 arcsec.

Terrascape protocol considers it critical to incorporate HMI in the methodology because it incentivizes maintenance and improvement of the structural integrity of the landscape.

The Terrascape credit engine maintains an up-to-date layer of HMI at 1 km resolution. The project developer will be required to provide the coordinates of the landscape through a shape file and the Terrascape credit engine will automatically calculate the HMI of that landscape.

The second attribute of ecosystem integrity is composition, which is measured through Biodiversity Intactness.

Biodiversity Intactness is usually measured using the Biodiversity Intactness Index (Scholes and Biggs, 2005). It is a measure of change in abundance of a set of species at a project site over the project period, relative to a reference baseline. Several challenges exist in estimating reference baseline. These challenges include (a) lack of historical data on what biodiversity was prior to human interventions across the whole planet (b) differences in reference biodiversity not just across different eco-regions within the same biome but also within different land uses in the same eco-region, limiting the ability to cross reference (c) different viewpoints on the reference period – should it be pre-Anthropocene, pre-industrial era, or about 1950 since when more recent declines in biodiversity started, at least in tropics and sub-tropics.

Moreover, in the context of Nature Credits, directly using available layers of modelled BII (Newbold, 2016) to measure changes in biodiversity intactness is not of much use because certain kind of interventions, which are important for reducing biodiversity loss, such as reducing poaching and hunting, removing invasive species, are unlikely to increase the modelled BII, no matter how much efforts are deployed on the ground. Another key challenge with modelled BII is that certain keystone species – particularly megaherbivores such as elephants – are critically important for maintaining ecological functions and processes. However, disappearance of one single species has no to minimal impact on modelled BII – at least in the short term. Therefore, the globally available layers of modelled BII and thus EII are of limited use in calculating site scale or landscape scale changes in these indexes.

To address these challenges, Terrascape protocol proposes a proprietary Terrascape Biodiversity Intactness Index (TBII), which is detailed in Annex 1. The proposed approach is chosen for several reasons.

  1. Greater collaboration with local communities and stakeholders in biodiversity surveys: Terrascape methodology maintains a balance between remote sensing and biodiversity surveys. Collecting biodiversity data through surveys often requires collaboration with the indigenous peoples and local communities in setting up camera traps, and acoustic devices, collecting eDNA samples, and conducting sign surveys. The experience clearly indicates that engaging communities in such surveys enables a positive behavioural change towards biodiversity conservation.
  2. Alignment with Global Biodiversity Framework: As mentioned earlier, the Terrascape BII (TBII) goes beyond modelling and brings the measurements as close to “original” BII ((Scholes and Briggs, 2003) as possible. The modelled BII, however, double counts the land use change attributes.
  3. It maintains a balance between having enough species to indicate an improvement in the overall biodiversity, while keeping the requirements of biodiversity data collection (and thus associated costs) to a manageable level. Therefore, when the population of keystone species, such as elephants, dwindles or recovers in the landscape, the TBII reduces or increases.

TBII is a proprietary index developed by Terrascape. Please contact us if you would like to know more about TBII.

The third attribute of ecosystem integrity is ecosystem function. Efforts to map ecosystem function have concentrated on diverse aspects of functional integrity. Some approaches have explored alterations in specific variables related to ecosystem function, yet no singular metric has been developed to comprehensively represent all dimensions of ecosystem function. In the absence of an alternative, more encompassing methodologies, the Terrascape protocol directs its focus toward a key ecosystem function, namely Net Primary Productivity (NPP), due to its well-established links with ecosystem functioning (Malhi et al., 2011; Mayer et al., 2021), as well as its advantages in terms of spatial resolution (layers available in raster format at 1 km² resolution or higher) and update frequency (e.g., MODIS releases a global new NPP layer annually).

Initially, a global layer of potential NPP is created to serve as a ‘natural’ reference. This layer is then juxtaposed with a current-day NPP layer derived from remote sensing to assess proportional losses in NPP. Natural NPP levels are modelled per grid cell using environmental variables trained on mean NPP levels (Running and Zhao, 2015) measured within strictly managed protected areas (IUCN categories I and II) between 2015 and 2020 (UNEP-WCMC and IUCN, 2017).

A generalized linear model framework is employed, using a Gamma distribution for the response variable and a log link. Model selection follows a backwards stepwise approach based on AIC values (Zuur, 2009). Variables are chosen for testing through a literature review of potential predictors of NPP, including latitude, bioclimatic variables (Fick and Hijmans, 2017), mean, minimum, and maximum solar radiation (Fick and Hijmans, 2017); aridity (Global Aridity Index, Zomer and Trabucco, 2022); total nitrogen, cation exchange capacity, predicted sand concentration, pH of water in soil (Poggio et al., 2021); continuous heat insulation load index (CHILI, Theobald et al., 2015); roughness of terrain, slope, topographic position index, terrain ruggedness index (Amatulli et al., 2018); and landforms (Sayre et al., 2020). The final model structure incorporates latitude as an interaction with total annual precipitation, mean annual temperature, and the mean temperature of the coldest quarter.

For each grid cell, the ratio of retained functioning is computed by dividing the current-day NPP value by the natural (model-estimated) NPP value.

The Terrascape credit engine maintains a global up-to-date layer of NPP ratio. Based on the geographical coordinates of the landscape, the Terrascape credit engine will calculate the NPP ratio.