• HOME
  • News
  • New models help estimate global biodiversity

New models help estimate global biodiversity

2018-01-26
興新聞張貼者
Unit秘書室
1,069

New models help estimate global biodiversity


Source:2018-1-24/Earth/Kay Vandette

To fully understand the effects that climate change, deforestation, and conservation efforts are having on different ecosystems, it’s important to know and account for all the different species that live on Earth.

That’s why accurate measurements of biodiversity across the globe are becoming more and more of a priority.

But due to the enormous scope, biodiversity has been proven difficult to measure, and biodiversity surveys can be costly and difficult to conduct.

As such, experts are now turning to biodiversity upscaling, which is the process of estimating species’ populations across a large area based on a relatively small sample of surveys.

Many different methods have been suggested for biodiversity upscaling, but whether or not these efforts could successfully map biodiversity across the globe is still up for debate.

A new study published in the journal Ecological Monographs put 19 different techniques for biodiversity upscaling to the test using one data set.

The study asked researchers who had created a biodiversity upscaling method to test their system by applying it to the 1999 Great Britain Countryside Survey.

The results were then compared with the true species-area relationship of plants in great Britain, or the accurate biodiversity of plant species in the area, to see which method shows the most promise for measuring global biodiversity.

The model that seemed to have the most success was a sampling theory created by Fangliang He from the University of Alberta, Canada and Tsung-Jen Shen from the National Chung Hsing University in Taiwan.

The sampling theory made estimates that were within a ten percent range of the true biodiversity of species. However, this theory proved poorly suited to measuring biodiversity in smaller areas.

Two other models also performed well, but some models were not even close to gauging the 2,3000 plant species of Great Britain’s ecosystem. The estimates ranged from to 62 species in total to 11,593.

The results, while greatly varied, are still promising as the three models that came close to the real data could pave the way for a global upscaling measurement method that accurately estimates biodiversity.

“We have shown that mathematical modeling of biodiversity upscaling has come of age,” said William Kunin from the University of Leeds and study’s lead author. “These methods will greatly facilitate biodiversity estimation in poorly-studied taxa and regions and the monitoring of biodiversity change at multiple spatial scales.”


Global modelling of biodiversity now possible


Source:2018-1-25/AgriNews
A mathematical model developed by Prof Cang Hui at Stellenbosch University (SU) has proven to be the single best method, from several tested worldwide, for estimating the biodiversity of plants over a large area.

Models are crucial tools that allow scientists to estimate the biological diversity of particular habitats, regions, countries and even continents, and to assess how this might be changing over time.

Prof Hui was part of an international effort involving five research groups who were asked to test the accuracy of their modelling techniques by applying it to small samples from the same dataset – the 1999 Great Britain Countryside Survey. Their predictions were then tested against data from the national database of British plant species.

This provided the ‘true’ species-area relationship for British plants, enabling the research team to determine the best modelling technique. It is the first time that these mathematical techniques could be tested, and compared, on such a large scale. The results of the study were published in the journal Ecological Monographs this week.

Top performing models
Of all the models tested, the single best method for estimating the shape of species-area relationship was that of Prof Hui, based on his concept of species’ occupancy ranking. It is also the first time for this model to be published.

Prof Hui’s research group in the Department of Mathematical Sciences at SU focuses on developing models and theories for explaining emerging patterns in ecology. “As ecological processes are highly complex and adaptive, we rely on the simplicity of mathematical language to build models and theoretical frameworks,” he explains.

Another top performing model was that of Prof Fangliang He (University of Alberta, Canada) and Prof Tsung-Jen Shen (National Chung Hsing University, Taiwan), which provided estimates within 10% of the true value.

The other models performed less well; while there are around 2 300 plant species in the area in question, some models’ upscaled species richness estimates were far off the mark, ranging from 62 to 11 593.

Policies and the preservation of biodiversity

Prof William Kunin, an ecologist from the University of Leeds and lead author on the article, says policymakers are often concerned with the preservation of biodiversity at national, continental or global scales, but most biodiversity monitoring is conducted at very fine scales.

“This mismatch between the scales of our policies and of our data creates serious challenges, especially when assessing biodiversity change.”

In this study, the task required estimating the biodiversity of an area five orders of magnitude larger than the total area sampled – equivalent to estimating the species richness of the land plants across the entire globe based on samples that cover only 3 000 km2.

The methods will greatly aid the work of the Intergovernmental Panel on Biodiversity and Ecosystem Services (IPBES). One of their aims is to provide policymakers with objective scientific assessments about the status of the planet’s biodiversity and its services to people. The Convention on Biological Diversity (CBD) also requires countries to improve their monitoring and reporting of biodiversity, as set out in the Aichi Targets.

Prof Kunin believes mathematical modelling of biodiversity upscaling has come of age. “These methods will greatly facilitate biodiversity estimation in poorly-studied taxa and regions, and the monitoring of biodiversity change at multiple spatial scales,” he concludes.


Accurate Estimation of Biodiversity Is Now Possible on a Global Scale


Source:2018-1-23/Science Newsline/Stellenbosch University
Source:2018-1-23/EurekAlert! Science News/Stellenbosch University

We know remarkably little about the diversity of life on Earth, which makes it hard to know with any certainty whether we're succeeding in our efforts to conserve it. The goal of the Intergovernmental Panel on Biodiversity and Ecosystem Services (IPBES) is to provide policymakers with objective scientific assessments about the status of the planet's biodiversity and its services to people. The Convention on Biological Diversity (CBD) has also set its ambitious Aichi Targets on better monitoring and reporting of biodiversity.

However, many countries and regions are limited in their capacity to do so as biodiversity surveys are difficult and extremely costly. Thus we need to design clever and robust methods to estimate the number of species in a large area from a limited number of small samples. Over the past two decades, a growing number of methods have been developed to attempt this, but until now most have only been shown to upscale by maximum two orders of magnitude in spatial scales, the equivalent of estimating the number of species in an area of a hundred square metres from a sample of only one square metre.

In a new study, published in Ecological Monographs today (Tuesday 23 January 2018), nearly the entire global research community addressing this problem was asked to put their techniques to the test by applying them to the same dataset - the 1999 Great Britain Countryside Survey. This represents a biodiversity upscaling of up to 10 orders of magnitude, equivalent to estimating the land plant species richness of the entire globe based on samples that together cover only six square kilometres.

More than a dozen methods belonging to five conceptual groups were tested, including the influential maximum entropy model developed by Prof John Harte at the University of California, Berkeley. The predictions of the models were then tested against the "true" species-area relationship for British plants, derived from contemporaneously surveyed national atlas data.

Prof William Kunin, an ecologist from the University of Leeds and lead author on the article, says policymakers are often concerned with the preservation of biodiversity at national, continental or global scales, but most biodiversity monitoring is conducted at very fine scales.

"This mismatch between the scales of our policies and of our data creates serious challenges, especially when assessing biodiversity change."

Of all the models tested, the model making the most robust estimates for total species richness was one based on the sampling theory developed by Prof Fangliang He (University of Alberta, Canada) and Prof Tsung-Jen Shen (National Chung Hsing University, Taiwan), which provided estimates within 10% of the true value. However, this model was not appropriate for estimating the shape of the "species-area relationship" - making it a poor choice for estimating the number of species found in areas smaller than Britain as a whole. The single best method for estimating the shape of species-area relationship was proposed by Prof Cang Hui from Stellenbosch University, based on his concept of species' occupancy ranking. A third model, proposed by Dr. Arnošt Šizling (of the Czech Academy of Sciences), combined well with the Shen-He method to allow even closer estimates of this curve.

Other models performed less well; while there are around 2,300 plant species in area in question, some models' up-scaled species richness estimates were far off the mark, ranging from 62 to 11,593.

Prof Kunin says while there remains substantial room for improvement in upscaling methods, the results suggest that several existing methods have the potential for practical application to estimate species richness at coarse spatial scales.

"We have shown that mathematical modelling of biodiversity upscaling has come of age. These methods will greatly facilitate biodiversity estimation in poorly-studied taxa and regions, and the monitoring of biodiversity change at multiple spatial scales," he concludes.
Back
TOP