Measuring Biosphere Health – From Satellite Proxy to Full Metric

The Importance: Humanity urgently needs reliable ways to measure the health and stability of the global biosphere. Existing metrics within frameworks like the Planetary Boundaries often focus on pressures (like land use change) or lagging indicators (like extinction rates). While valuable, these don’t fully capture the functional integrity of ecosystems—how well they are processing energy and sustaining life across trophic levels. We lack a comprehensive, predictive “dashboard” to monitor the biosphere’s condition in near real-time and provide early warnings of potential collapse. Developing such a metric is crucial for guiding policy, prioritizing conservation efforts, and assessing the effectiveness of interventions.

The Approach – Part 1: Developing the SPPPI (Satellite-Derived Primary Production Pressure Index): Given the urgency and the availability of global satellite data, the first phase focuses on creating a robust proxy metric – the SPPPI. This index targets a key component of biosphere stress: human pressure on Net Primary Production (NPP), the energy base created by plants.

The SPPPI development follows these steps:

1. Calculate Proxy HANPP (Estimate Total Human Pressure): Using established methods and global satellite datasets (e.g., measurements of plant greenness and land cover maps), we estimate the total Human Appropriation of Net Primary Production (HANPP). This involves two main parts:
   • Estimating Actual Plant Growth (NPPₐ): Using satellite measurements to see how much plants are growing right now.
   • Estimating Potential Plant Growth (NPPₚ): Using computer models or data from undisturbed natural areas to figure out how much could grow there without human changes.
   • Growth Lost because of Land Change: We compare how much plant growth could naturally happen in an area (NPPₚ) with how much is actually growing there now (NPPₐ). The difference is the plant growth we’ve lost just by changing the land type (like replacing a forest with a farm).
   • Estimating Harvested Plant Growth: We look at the plants that are currently growing in human-managed areas (like crops or timber forests) (NPPₐ) and estimate what fraction of that growth humans take for their use (the harvest). We find these average harvest fractions in scientific studies. This part requires careful research and AI tools for synthesis.
2. Calculate SPPPI (The Pressure Index):
   • First, Sum the Pressures: Add the two parts calculated above: (Growth Lost because of Land Change) + (Harvested Plant Growth). This sum gives the Total Proxy HANPP – our best satellite-based estimate of the total plant growth humans are preventing or taking.
   • Then, Calculate the Index (SPPPI): Take that Total Proxy HANPP amount and divide it by the Potential Natural Plant Growth (NPPₚ) for that same area. Finally, express this result as a percentage. This percentage tells us how much of nature’s potential plant growth is being used or prevented by human activities in that area.

1. Map and Analyze: Generate global maps of SPPPI and analyze spatial patterns and temporal trends. Compare results to existing HANPP studies for basic validation.
2. Publish with Caveats: Disseminate the SPPPI methodology and results through scientific publication. Crucially, this publication must clearly state the limitations: SPPPI only measures pressure on primary production; it does not account for energy transfer efficiency between trophic levels or nutrient imbalances (stoichiometry). It is an indicator of pressure, not a full measure of integrity.

The Approach – Part 2: Validating the Full Biosphere Integrity Metric (BIM): The SPPPI is a necessary but insufficient step. The ultimate goal remains the development and validation of the full BIM, which integrates trophic efficiency and stoichiometry for a truly functional assessment of biosphere health.

Achieving this requires moving beyond satellite-only data:

1. Integrate Ground Data: Combine SPPPI data with field measurements from diverse ecosystems (e.g., LTER sites, targeted ecological surveys). This data is needed to estimate:
   • Trophic Efficiency (Eᵢ): Energy transfer between levels, using biomass measurements, stable isotope analysis, or metabolic studies.
   • Stoichiometric Correction (α): Nutrient ratios (e.g., N:P) in water, soil, and organisms to assess imbalances.
2. Develop Integrated Models: Use advanced modeling techniques, including AI/machine learning (like the proposed CNNs ), trained on both satellite and field data to estimate the full BIM (TII adjusted by α) across different landscapes and globally.
3. Rigorous Validation: Test the BIM’s predictive power by comparing its outputs against documented ecosystem regime shifts or collapses in historical datasets or long-term monitoring sites. Assess its ability to provide reliable early warning signals.
4. Collaboration: This phase requires collaboration with ecologists, modelers, remote sensing specialists, and data scientists with access to necessary data and computational resources. The SPPPI publication should explicitly serve as a call for such collaboration.

By pursuing this two-part approach, we can provide an urgently needed indicator (SPPPI) in the short term, while laying the groundwork and building momentum for the comprehensive, validated Biosphere Integrity Metric (BIM) required for understanding and navigating the biosphere crisis.