Quantifying biodiversity and maximising species persistence during offsetting

Date: 01, Nov, 2020
Author(s):   Marshall, E.
Publisher: The University of Melbourne

PhD Thesis

Biodiversity is declining globally, with habitat clearing playing a major role in perpetuating these declines. Offsets aim to achieve no net loss of biodiversity by implementing conservation actions that deliver equal biodiversity gains to those lost through development. Broad habitat-based biodiversity metrics are commonly used to quantify development impacts and assign offset requirements. However, it is unclear what reliance on habitat-based offset metrics means for biodiversity long-term. In this thesis I explore the current state of biodiversity metrics within the scientific literature and how these metrics are applied in policies around the world. I also quantitatively test nine biodiversity metrics and explore the long-term ramifications of their use in offsetting on species persistence.

In a sample of 255 publications from ecology (n = 158), conservation planning (n = 54), and offsetting (n = 43), I identify 24 categories of metrics used to quantify biodiversity. The offsetting literature focused largely on habitat attributes and area-based approaches for measuring biodiversity. Similarly, consistent use of habitat attributes, habitat condition, and area in 21 offset policies demonstrates that offsets do not adequately capture individual species or communities. Many offset policies measure species presence, however, less than half of those I reviewed measured any species-specific attributes which could be used to help inform conservation actions for those species. These two reviews demonstrate that the metrics currently used to measure biodiversity don’t reflect some of the key biodiversity attributes offsets aim to protect.

To understand the long-term consequences of relying on such habitat-based metrics for offsetting I developed a spatial simulation tool and present a methodological framework that quantitatively tests the effects of metric choice on long-term persistence. The R-based simulation tool uses raster data to simulate development impacts and restoration efforts. I tested nine biodiversity metrics spanning an axis of pattern versus process and capturing different levels of biodiversity: area of habitat, condition of habitat, vegetation area, vegetation condition, area * habitat suitability, condition * habitat suitability, abundance, metapopulation connectivity and rarity-weighted richness. The resulting raster outputs are used in population viability analyses for five species. Most metrics achieved no net loss or net gains in the metric values, species’ habitat suitability or abundance, but only when impacts avoided high suitability areas. When impacts cannot avoid high suitability areas, species-specific metrics deliver higher gains in abundance per hectare restored than habitat-based metrics alone.

Failing to improve current offset practices ensures species will continue to decline under development-offset trading programs and should provide an incentive for policy makers to properly enforce impact avoidance measures where possible.