As we’ve set out before, biodiversity is a critical concept - nothing less than the life of our planet – and is such an important concept it is actually defined in a UN Treaty. But how do we measure such a complex idea?
Well, as Facebook once said, ‘it’s complicated’. So let’s dive in and get to grips with what biodiversity is and how it’s measured.
A note of caution!
The key point at the start – these concepts are NOT the same as the concepts in the Biodiversity Metric.
It’s really important to stress that the Biodiversity Metric – the tool that will measure biodiversity on different sites for legal purposes – has its own distinct set of requirements and rules. We have set out how the metric works in many other blogs.
If you’re interested in understanding how the metric works please read some of our other blogs. The below is a detailed dive into the concepts that underpin the academic concept of biodiversity – it won’t help with the metric!
With that all said, let’s dive in.
Biodiversity - the basics
It's critical to emphasise from the get-go that biodiversity - and the means by which we gauge it - is a multifaceted notion. In some ways, it’s easier to embrace the abstract notion that biodiversity is a complex tapestry, crafted with innumerable threads of life. Each thread signifies a unique species, each design an ecosystem, and each colour strand the genetic diversity within species.
What do we mean by ‘species’? Well, Ernst Mayr’s biological species concept delineates a species as 'groups of interbreeding natural populations that are reproductively isolated from other such groups.’
But how do we take this definition and use it to calculate this incredible variety of life forms on our planet? Let's delve into the primary gauges of biodiversity with a brief overview of the main academic and industry methods used to assess biodiversity. Please note that this is just an introduction to some of the approaches - numerous other tools, measures, and methods are available to ecologists, each with its unique viewpoint and each catering to specific facets of biodiversity.
Getting the raw data and measuring species richness
In all cases, we begin by gathering data through meticulous surveys. This initial step entails identifying the variety of species present at a given site, along with the count of each species' individuals. But, the data collected is just raw material; it's like having a book with its pages scattered. The essence lies in arranging, processing, and analysing this data to reveal the biodiversity story. The second step takes us into the realm of data visualisation and statistical tools.
First, we want to get an idea of species richness. This measures the number of species per sample. The more species present in a sample, the 'richer' the sample. Species richness as a measure on its own takes no account of the number of individuals of each species present – thus, one daisy has as much influence on the richness of an area as 100 buttercups. Richness is like counting the different types of books in a library – it gives us a sense of the variety, but not of the volume or distribution. Note that this is not the same as biodiversity, though it does underpin it.
One of the basic tools used for the comparison of diversity in different sample sizes is the rarefaction curve. Imagine this as a graph, where species are plotted against samples. A steeper slope suggests that there are many more species waiting to be unveiled, much like an unexplored book laden with numerous chapters. If the curve grows progressively flat towards the right, it suggests a substantial number of species have been sampled, and further exhaustive sampling might only expose a handful of new species.
A rank-abundance curve (or a Whittaker plot) also presents a valuable tool. It's akin to a chart that eloquently displays contrasting patterns of species richness. The shape of this graph can be employed to infer which species abundance model best describes the data - a steep curve demonstrates dominance while shallower curves demonstrate evenness.
Relative species abundance refers to how common or rare a species is, relative to other species in a defined location or community. Usually, relative species abundances are described for a single trophic level – because such species will likely compete for similar resources. Essentially, it provides an idea about the distribution of individuals among the species in a given ecosystem. In simple terms, imagine a field where you spot both daisies and buttercups. The count of each species tells you their relative abundance. If there are 30 daisies and 70 buttercups, it indicates that buttercups are more abundant.
Fisher's logarithmic series model provides a mathematical depiction of the relationship between the number of species and the number of individuals within that species. It shapes the way we perceive and represent the abundance of species.
Applying appropriate models and tools
As we can already see, there are a lot of different ways to measure biodiversity. But it now gets even more complex as we now need to pick how we will process this data. Diversity indices, mathematical expressions encapsulating species richness and evenness, and heterogeneity measures, tools that amalgamate the richness and evenness components of diversity, are all routinely utilised by ecologists to measure and evaluate biological diversity.
What is the best approach to measuring biodiversity? Researchers Smith and Wilson (1996) suggested four indispensable requirements and ten appealing characteristics for an ideal measure. The absolute necessities imply that the measure ought to be independent of species richness and responsive to shifts in the abundance of the least abundant species. Additionally, incorporating a rare species into the community should diminish the measure, and it should stay unaffected by the units utilised to measure it.
There's no 'one-size-fits-all' measure for biodiversity. The measure you elect to utilise largely depends on the facet of biodiversity you're interested in focusing on. A plethora of inappropriately used measures can never substitute for the correct measure used prudently. Understanding the distinction between species richness and biodiversity, though frequently confused, is one such instance.
Common tools include the Simpson’s Diversity Index and the Shannon-Wiener Index - these indices are mathematical formulas that encapsulate both species richness and the evenness of individuals among the species present, thus providing a more detailed picture of biodiversity.
Simpson’s Index, devised by Edward Hugh Simpson in 1949, measures the probability that two individuals randomly selected from an area will belong to the same species. It takes into account both species richness and evenness among the species present. This index is recognised as one of the most robust and meaningful diversity measures available. In essence, it measures the diversity by looking at the probability that any two individuals drawn at random from an infinitely large community belong to the same species.
The Shannon-Wiener Index, developed independently by Claude Shannon and Norbert Wiener, has roots in both linguistic and information theory. It quantifies the uncertainty in predicting the species identity of an individual that is taken at random from the dataset. Despite its popularity, the Shannon-Wiener index has been criticised for its sensitivity to sample size.
These advanced indices not only count the number of different species (richness) but also look at how evenly the individuals are distributed among these species (evenness). Evenness is a measure of the relative abundance of the different species making up the richness of an area. A forest with 5 species each represented by 20 individuals has greater evenness than another with the same 5 species but with individual counts of 50, 10, 10, 10, and 20.
Going beyond the standard measures
Beyond these fundamental academic instruments and measures, there's an assortment of standards, evaluation methods, and metrics for managing biodiversity. The BSI Group published 'BS 42020 Biodiversity in planning and development' – a code of practice that presents a methodology for biodiversity management. This standard endeavours to ensure the quality and appropriateness of ecological information submitted with planning applications, thereby promoting transparency and consistency.
The Building Research Establishment Environmental Assessment Method (BREEAM) is another crucial tool in our arsenal. It's an evaluation method for master planning projects, infrastructure, and buildings. Similarly, the Civil Engineering Environmental Quality and Award Scheme (CEEQUAL) appraises a wide array of economic, environmental, and social matters, including a project or contract’s impact on neighbours and community relations.
On an international scale, ISO 14000, developed by the International Organization for Standardization, furnishes a framework for companies and organisations aspiring to manage their environmental responsibilities. Additionally, the Leadership in Energy and Environmental Design (LEED), developed by the non-profit U.S. Green Building Council, establishes a suite of rating systems for the design, construction, operation, and maintenance of green buildings, homes, and neighbourhoods.
Approaches like Habitat Hectares, initially devised in Victoria, Australia, serve as examples of multiple attribute metrics specifically designed for offsetting. The Habitat Hectares approach assesses various attributes of the habitat against benchmarks representing the average characteristics of mature stands of native vegetation of the same community type in a 'natural' or 'undisturbed' condition. Similarly, the Treweek Matrix is another method through which offsets are designed qualitatively through an Environmental Impact Assessment (EIA). This Matrix is the system that underpins the Biodiversity Metric.
As we conclude our journey, it becomes evident that measuring biodiversity is not a straightforward task but a complex process of data collection, analysis, and the prudent application of diverse tools. Much like peeling an onion, each layer offers a fresh perspective and contributes to our overall understanding of this grand tapestry of life. Bear in mind, this overview only grazes the surface – there is a lot more to discover about how we measure biodiversity, just as there is so much more to learn about life on Earth.