DOC's conservation strategies are used to manage and protect areas such as the Pekapeka wetlands. Photo Credit: Shellie Evans ©

Priorities for conservation of NZ’s ecosystems and species

“Ben helped us start to think outside of the limitations of running this analysis on our local machine to considering the possibilities of running hundreds and thousands of iterations."

Imagine trying to complete a jigsaw puzzle, but using pieces that constantly change their shape. Every few years, New Zealand’s Department of Conservation (DOC) has a puzzle like that to assemble in order to make decisions around conservation strategy and allocation of conservation resources.

DOC’s puzzle pieces are divided into two categories: Ecosystem Management Units (EMUs) and Species Management Units (SMUs). EMUs are places where DOC could work to maintain a wide range of ecosystems as well as the security of threatened species. SMUs are places where extra management is required for security of particular species.

It’s no small task to assemble this puzzle, especially since the characteristics of the pieces change from year to year and there are lots of different values that determine a ‘good fit’. DOC uses a specialised conservation planning software called Zonation to handle the bulk of the work. This year, DOC also enlisted NeSI computing resources and data management expertise to help tackle the challenge of processing and analysing the data.

“What the Zonation program does is, we feed it a range of information about the different species and ecosystems that occur at each management unit and we have a number of input parameters that we can tweak to provide us a ranked, hierarchical list of sites to tell us what sites are best to manage under a different range of circumstances,” says David Burlace, Technical Advisor in Planning, Monitoring & Reporting, Science & Policy at DOC.

“In order to play with all these parameters and get a feel for what settings are the optimum for our analysis purposes, we’ve been running many different scenarios with different weights on the input parameters. The computation for a single run was taking up to two hours on our local machine. Now we’re at a point where we’ve run up to 1,000 different scenarios with NeSI, which would have been completely unfeasible with DOC’s internal resources.”

The prioritisation list covers more than 500 species, and includes nearly 1,400 management units ranging in size from one hectare to more than 50,000 hectares. The candidate management units are identified by panels of in-house and external experts, and collectively they provide examples of nearly all New Zealand’s ecosystem types, ranging from coastal pohutukawa to tussock grasslands to braided rivers. Many of the management units contain several valuable ecosystem types.

Ranking is dependent on each ecosystem’s condition, which is determined by the pressures and pests known to be present, as well as the benefits of past management. Ranking also considers the potential for an ecosystem’s condition to improve if management is initiated or intensified, or lose integrity if management is discontinued or scaled back.

“Our goal is to ensure that our management intervention protects a full range of ecosystems and ensures threatened species persistence,” says Mr. Burlace. “With this sort of system, we can get an objective view to make sure that we’re accounting for everything that needs to be, and to ensure that a broad range of ecosystems and species are being managed.”

Ben Roberts, a member of NeSI’s Solutions Team, has been working with DOC’s Planning, Monitoring and Reporting team. In addition to offering technical assistance and automating parts of the analysis process, Dr. Roberts has also shared valuable advice on data management tactics.

“Ben helped us start to think outside of the limitations of running this analysis on our local machine to considering the possibilities of running hundreds and thousands of iterations. It’s really helped to broaden our critical thinking about how we’re approaching the analysis,” Mr. Burlace says. “He’s been really good at providing advice on how to tackle a project of this nature, and how to structure our workflows in order to manage the amount of data going in and coming out.”

The project is drawing to a close as the team is aiming to have a final set of rankings complete by early 2018. There are other puzzles to be solved, however, both in terms of further exploring the values represented by different Zonation scenarios and in terms of improving the quality and completeness of underlying ecosystem models. Mr. Burlace says DOC may call upon NeSI’s support to tackle some of those projects as well.

“We can write increasingly more sophisticated models but in order to do that, we need to continue to do this comprehensive analysis to make sure we’re using the correct weighted list of parameters,” he says. “Through this project, we’ve already begun to see the benefits of using the NeSI platform for some other projects we would like to get underway in the future.”

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